{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  THIS IS THE PRIMARY VERSION TO USE FOR ALL STATES  #from WA 5/18/24\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):  #from IN\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    The optional xScale parameter is the ratio of longitude to latitude lengths scales (<<1 for far from equator)\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a 4-tri polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*12                      #xScale has same meaning as in buildWedge\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]  \n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]/XSCALE*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]/XSCALE*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def buildArcPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a fuller polygon from four HD wedges emanating from the centerpoint\n",
    "    twoPi = 2. * 3.1415926   #xScale has same meaning as in buildWedge\n",
    "    POINTS = list()                   \n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW] % twoPi                 #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ] % twoPi \n",
    "        midAngle = [0.75*ccwAngle + 0.25*cwAngle , 0.25*ccwAngle + 0.75*cwAngle ]  #avoid s sampling cone center for wide angles\n",
    "        if abs (ccwAngle - cwAngle) > 3.1415926 :  #angles straddle angle=0\n",
    "            midAngle = [0.75*(ccwAngle - twoPi) + 0.25*cwAngle , 0.25*(ccwAngle -twoPi) + 0.75*cwAngle ]\n",
    "        angList = [ccwAngle] + midAngle + [cwAngle]\n",
    "        for ang in angList:\n",
    "            POINTS.append(Point(CP.x + RADII[nW]/XSCALE*math.cos(ang), CP.y + RADII[nW]*math.sin(ang) ) )\n",
    "                          \n",
    "    POLLY = Polygon(POINTS)\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - DO WE NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ??  #\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections count only if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     new for MN 4/7/24 - don't enforce contiguity here -- too slow -- fix in cleanup stage instead\n",
    "     \"\"\"\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        tryList = getAdjoiners(addedList,unitNbrs)\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP :  #and wontEnclave(UU, addedList, unitNbrs, borderUnits) :  #we'll post-fix contig'y\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:  #stop looping if no new neighbors found on previous loop\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=4):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def avoidedEnclave(UNITLIST, UNITNBRS, ADDLIST,MAXLOOPS=15):  #20 is arbitrary, but does suppress slender chains\n",
    "    \"\"\"\n",
    "    This method (new for WI 5-23-24) is designed as a shorter check than enclaveCheck for legitimacy of adding ADDLIST to UNITLIST\n",
    "    It tries to find contiguity among all ADDLIST's neighbors that won't be in the UNITLIST after the add.\n",
    "    It does this in successive loops, growing from one non-UNITLIST neighbor in loops to all its non-UL neighbors\n",
    "    If success before MAXLOOPS, it returns True (i.e. this list addition avoided forming an enclave), else it returns False\n",
    "        Note that this method will not usually allow a UNITLIST that doesn't currently touch map border to start touching it\n",
    "        (too many loops to go all the way around the UNITLIST to find the complement's connection)\n",
    "    \"\"\"   \n",
    "    willBeInUnitSet = set(UNITLIST+ADDLIST)\n",
    "    nbrsOfADDLIST = set()\n",
    "    for U in ADDLIST:\n",
    "        nbrsOfADDLIST = nbrsOfADDLIST.union(set(UNITNBRS[U]))  #these are the neighbors of the units we plan to add to UNITLIST\n",
    "    nbrsOfADDLIST = nbrsOfADDLIST.difference(willBeInUnitSet)\n",
    "    if len(nbrsOfADDLIST) == 0:\n",
    "        raise Exception(\"ERROR! Attempted to add list\",ADDLIST,\"but it should have been flagged previously as an enclave\")\n",
    "    firstNo = next(iter(nbrsOfADDLIST))  #pick one of these non-UL neighbors as a starter\n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfADDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnect = False\n",
    "    if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still DIRECTLY connect after the add\n",
    "        stillConnect = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnect:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.difference(willBeInUnitSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfADDLIST)  #running list of complement-connectable non-UL neighbors of ADDLIST\n",
    "        if len(foundNbrSet) == len(nbrsOfADDLIST):  #ALL non-UNITLIST neighbors still connect after the add\n",
    "            stillConnect = True\n",
    "    return stillConnect\n",
    "              \n",
    "\n",
    "def avoidedIsland(UNITLIST, UNITNBRS, SHEDLIST,MAXLOOPS=15):\n",
    "    \"\"\"\n",
    "    analogous to avoidedEnclave but for shedding a list from UNITLIST; we look to connect in-UNITLIST neighbors after the proposed shed\n",
    "    \"\"\"\n",
    "    shrunkSet = set(UNITLIST).difference(set(SHEDLIST))  #shorthand for the proposed unitlist after shedding\n",
    "    nbrsOfSHEDLIST = set()\n",
    "    for U in SHEDLIST:\n",
    "        nbrsOfSHEDLIST = nbrsOfSHEDLIST.union(set(UNITNBRS[U]))\n",
    "    nbrsOfSHEDLIST = nbrsOfSHEDLIST.intersection(shrunkSet)\n",
    "    if len(nbrsOfSHEDLIST) == 0:\n",
    "        raise Exception(\"ERROR! Attempted to shed list\",SHEDLIST,\"but it was never connected to the rest of the unit list\")\n",
    "    firstNo = next(iter(nbrsOfSHEDLIST))  #pick one of these still-in-UL neighbors as a starter   \n",
    "    firstGroup = getContigFromStarter(firstNo, nbrsOfSHEDLIST, UNITNBRS) #first find all neighbors that directly connect\n",
    "    foundNbrSet, foundTotalSet, newFoundSet = set(firstGroup),set(firstGroup),set(firstGroup)\n",
    "    LOOPNO = 0\n",
    "    stillConnects = False\n",
    "    if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #ALL in-UNITLIST neighbors of the shedlist still DIRECTLY connect after the shed\n",
    "        stillConnects = True\n",
    "    while len(newFoundSet) > 0 and LOOPNO <= MAXLOOPS and not stillConnects:\n",
    "        LOOPNO +=1\n",
    "        lastFoundSet = newFoundSet\n",
    "        newFoundSet = set()\n",
    "        for U in lastFoundSet:\n",
    "            newFoundSet = newFoundSet.union(set(UNITNBRS[U]))\n",
    "        newFoundSet = newFoundSet.intersection(shrunkSet)\n",
    "        \n",
    "        foundTotalSet = foundTotalSet.union(newFoundSet)\n",
    "        foundNbrSet = foundTotalSet.intersection(nbrsOfSHEDLIST)\n",
    "        if len(foundNbrSet) == len(nbrsOfSHEDLIST):  #all in-UNITLIST neighbors still connect after the shed\n",
    "            stillConnects = True\n",
    "    return stillConnects\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 6, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  WI\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use wi_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. WI has 5893718 peeps and is divided into 7059 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 72 counties in WI .  I will assign them county Nos 0 - 71\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Building county geom for county 40\n",
      "Building county geom for county 60\n",
      "Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 2 unpopulated coastal tracts.\n",
      "Lets plot them and their parent counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "if origMAP.geom_type == dummyPoly.geom_type:\n",
    "    mapExterior = origMAP.exterior\n",
    "else:\n",
    "    for i,geo in enumerate(origMAP.geoms):\n",
    "        if i == 0:\n",
    "            mapExterior = geo.exterior\n",
    "        else:\n",
    "            mapExterior = mapExterior.union(geo.exterior)\n",
    "\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(mapExterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.\")\n",
    "if len(skipList) > 0:\n",
    "    print(\"Lets plot them and their parent counties\")\n",
    "    for t in skipList:\n",
    "        plotPoly(tractGeom[t])\n",
    "        plotCenter(t,tractGeom[t],6)\n",
    "    plotPoly(origMAP,0.2)\n",
    "    for c in range(nCounties):\n",
    "        if isAlteredCounty[c]:\n",
    "            plotPoly(countyGeom[c])\n",
    "    plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 2 units will be axed\n",
      "here is the proposed skipList [3852, 3505]\n",
      "here is the final skipList [3852, 3505]\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [146, 3084] #...  #alter here if needed - other two for WA are not worth cutting out\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "removing coastal units from countyNo 53\n",
      "removing coastal units from countyNo 64\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.71263\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8a562a21-4107-4a3c-a320-90442a473387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\n",
      "unit 3739 is a true island.  We will move it to adjoin the mainland in same county.\n",
      "unit 3759 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 3068 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 3097 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 1006 is a true island.  We will move it to adjoin the mainland in same county.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RUN THIS ONLY IF WE FOUND POPULATED ISLANDS\n",
    "nSubGeoms = len(MAP.geoms)\n",
    "subGeoms = [MAP.geoms[n] for n in range(nSubGeoms)]\n",
    "subAreas = [subGeoms[n].area for n in range(nSubGeoms)]\n",
    "mainSubGeomNo = subAreas.index(np.max(subAreas))\n",
    "mainGeom = subGeoms[mainSubGeomNo]\n",
    "nonMainGeom = dummyPoly\n",
    "for geo in subGeoms:  #the \"nonMainGeom is all pieces of the state not in the biggest piece\n",
    "    if geo != mainGeom:\n",
    "        if nonMainGeom == dummyPoly:\n",
    "            nonMainGeom = geo\n",
    "        else:\n",
    "            nonMainGeom = nonMainGeom.union(geo)\n",
    "        \n",
    "print(\"Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\")\n",
    "hasIsland, isIsland = [False for c in range(nCounties)], [False for c in range(nCounties)]\n",
    "isIsland =  [False for t in range(nTracts)]\n",
    "islandXshift, islandYshift = [0. for t in range(nTracts)], [0. for t in range(nTracts)]\n",
    "islandList = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(nonMainGeom):  #this county contains an island.  Find all its island tracts\n",
    "        hasIsland[c] = True\n",
    "        if countyGeom[c].disjoint(mainGeom):  #need to connect the whole county\n",
    "            print(\"county\",c,\"is completely disconnected from mainland.  Move it to adjoin mainland\")\n",
    "            isIsland[c] = True\n",
    "            countyDist = [999999. for cc in range(nCounties)]  #default, to avoid picking island counties as closest to this one\n",
    "            for cc in range(nCounties):\n",
    "                if countyGeom[cc].intersects(mainGeom):\n",
    "                    countyDist[cc] = countyGeom[c].distance(countyGeom[cc].intersection(mainGeom) )\n",
    "            closestCounty = countyDist.index(np.min(countyDist))\n",
    "            p1, p2 = nearest_points(countyGeom[closestCounty],countyGeom[c])\n",
    "            for t in countyTractList[c]:\n",
    "                islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "            for t in countyTractList[c]:\n",
    "                plotPoly(tractGeom[t])\n",
    "                plotCenter(t,tractGeom[t])\n",
    "                plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                tractCP[t] = tractGeom[t].centroid\n",
    "                tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                plotPoly(tractGeom[t],0.2)\n",
    "        else: #move only the county's island tracts to connect with main geom\n",
    "            mainCountyGeom = countyGeom[c].intersection(mainGeom)\n",
    "            plotPoly(mainCountyGeom)\n",
    "            plotCenter(c,mainCountyGeom)\n",
    "            for t in countyTractList[c]:\n",
    "                if tractGeom[t].intersects(nonMainGeom) and t not in skipList:\n",
    "                    if tractGeom[t].intersects(mainCountyGeom):\n",
    "                        print(\"unit\",t,\"has island pieces.  We will reduce the tract to its main state component\")\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "                        tractGeom[t] = tractGeom[t].intersection(mainCountyGeom)\n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                    else:    \n",
    "                        isIsland[t] = True\n",
    "                        print(\"unit\",t,\"is a true island.  We will move it to adjoin the mainland in same county.\")\n",
    "                        islandList.append(t)\n",
    "                        if tractGeom[t].geom_type != dummyPoly.geom_type :  #island tract is multiple geoms.  collapse to its largest isle\n",
    "                            isleGeos = [geo for geo in tractGeom[t].geoms]\n",
    "                            isleAreas = [geo.area for geo in isleGeos]\n",
    "                            biggestIsleNo = isleAreas.index(np.max(isleAreas))\n",
    "                            tractGeom[t] = isleGeos[biggestIsleNo]\n",
    "                            tractCP[t] = tractGeom[t].centroid\n",
    "                        p1, p2 = nearest_points(mainCountyGeom, tractGeom[t])\n",
    "                        islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                        plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                        tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9a94118d-5863-4458-b77a-67d18cf01c2c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\n",
      "This would need adjustment for multi-county islands like Michigan UP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with island triage - RUN ONLY WITH ISLANDS\n",
    "print(\"If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\")\n",
    "print(\"This would need adjustment for multi-county islands like Michigan UP\")\n",
    "for c in range(nCounties):\n",
    "    if hasIsland[c] :  #rebuild the county geom with the translated islands\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in countyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "MAP = countyGeom[0]\n",
    "plotPoly(countyGeom[0])\n",
    "for c in range(1,nCounties):\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "    plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": 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YEDqqFrpTPPbGRtZu2MADP/6xz9poffO36EkzsUV0LwprSpvYvLKSSefEkpA5MLLySiQSydmQAiXE0HUDR7OL95/IJzZWcM7V2YQnxHDo8718/PxhincXM++rszBZ3IJDCEHhznJ2vr+DoiIzFpOTvMlRjLlgIom+TD8vdAhhJ1lnSwthqkpYjI8SoAkBW54n7P6VPdhUsPpfXxIZ4WT6NTLniUQiGRxIgRIiFO4oZc3z22hqMaMbGqBy4T3nEJ8eAcCwyUlkrjzI528epezwxyy4Yw4NFfVseSefqmobyUk6i5aOZPjMIZgtfhAOhhHSIyiRSUmgadQVFhKTne3147eu/C9GZA5aUka32+5bc4Ti4xqX3z2+XXhKJBLJQEcKlBCg8lgD7z+5F7Axfk48YeECVRXEpYW3b6MoCmMXjyRlZCof/20tr/9mCwCZmRpX3DKBjFEJfq0irIjQDzMeN3482z74gPPuusvrxzY+/QOWbz7f7XbN9Q7Wvn6AkWOsZI1P9bodEolEEqxIgRICaGaV2OhWauttHN5Wxlf/cOEZxUbikGiu//WFlByowRpmJjnHS06vvUUYKCE8ggIwbOpUlv/3v14/rmPbpwhTGOZhE7rddu3zGwDBvNuCozihRCKR+AtZ/jSIMHSDvZ8fxd7s7LQ8JimMtGFuoRGXqHU7EqJpKlmjEwInTsDtJGsKbf1bceQIsZG9zwHTHa53fo7pkp90u13RrkoO7HIy96rhhEVZut1eIpFIBhKh3YMMMKpLm/j0xcN8+mIBaVkayRlW0icMo/hALXu3O5i8IJlZ13RfIfjZtUd4cnUBrU6Da6dm8qOLR2HqYQiyt1CEEdLFApvKyvjik5VcfP11Xj2uXnYYWk9gnbnkrNu5HDqrnt1CRrpg1HkjvGqDRCKRhAKh24MMQAxdeJ4plBYZlBa1sGP9bgDCbQ4mXjSi21wnn+wp5+fv7eH6aVkkRFr455rDxIab+b+Ffu7kDP+HGet1dgy7jikprF/+NgWrVrFi2TIWLVlC+hTvRs3YX/4RYuo3ut1uy9v5NDZpXHr/HL/6DkkkEkmwIAVKECE8+uTqH04lPj0CZ6vuLsuiG4RHW3oUwbFiTzmjUqP4zTVu/4a/ryrg9x8f8LtAUTD8lqhNGIKaNw/SvLkcAHNmJIlfHYvWy2kRQ9dZ+Ze/UFZVxc3f+57XE7SJ1gaUsm2E/d+LZ92upqyJrZ9VMmV+LHFpEV61QSKRSEIF6YMSTHgEismiYbGZiIi1EhlnJToxrMfhpbHhZqoa7dQ1O3Hqhg+N7QY/jqA076ikeXM5sVcMJ+G2sTjLmqh+7UCvjtFSXc3zDz2E2WZj6SOP+CR7rP31X+DKuADFfObzIoRg9TNfEhnhYOrVMueJRCIZvMgRlCBCeBRKf0b0b56Vzaubizjv959hM2uYVIXnvzHDSxb2HAX/+aA4CusxpYQTOTvdvcAlsB+o6fH+TZWVvPT445y3aBEjzj/fN0YaOux5l/D7vzjrZgfWHqX4uMZld03BZA7tMG2JRCLpD1KgBBOi+026Iys+nPfvmccrG4todepcOTmDcRk+yoZ6FhQh/JZJ1pQURtOmMuxH6zDF2dzFf3s44uSor+el3z/OoiUXM2z+fJ/Z6PzsaeymkdgSks64TWuTk7X/20/uKAtDJqT5zBaJRCIJBaRACUb66ROZGRfO9y/M844tfUTBAMU/M4gR01Np2VFJ5T92AqBGmEm6fXyP9i3ZsZPUuFifihMAx4Z3sV5w51m3WffiRlodZuZ9TeY8kUgkEilQgog2J1mlvwolWPBT9Ilq0Ui6cyKth2oQdh1bbixqeM/8X4QQqKrvhZRw2NESEs+6TdG+WhTVhi3qpO37vjxO8b4qZl8zhvBomQtFIpEMHqRACSY8CsVPAw8DCkVTCMuL7/V+AuEfISUM6MZpeNZXRrLixSLef3wtWWOSqCioomCvA4B9G7/gvBuGMfa8HN/bKpFIJEGA7AqDCOEFHxRJ73CWlOA4dMjn7SgY0I3T8MhzRpA7MZrjh52se7+EwgMthIUZLFg6EoAvXi+g5GANBzeWIgz5ZZFIJAMbOYISVLRF8QyQKZ4QwJSSgm3E2XPE1LTW8M6hd2hyNXFB9gWMiOtDThlhoPRgaGzRNyaTtbGM7PGJRMRYAbfz7GcvHsDlUnjr8W0ANDe4yBodT11lMzkTEuV3RiKRDDikQAkiBtIIisnVjLOlAXNYVKBNOSsKcKK29ozrT7Sc4IYPbqDOXodNs/FM/jM8ufhJZqXN6lU7AhXQu93OZNEYMy+j0zJbhJnFNw2hpRnqa3XyVxXzxWsH29dbLAa3PDofW0RoF2eUSCSSjkiBEkyczHQf8jjCk3HUnwh6gZI5cyaty5efcf3rB16nwdHAu1e+S4ItgSkvTOH2j28n/6v5vWpHCBWEq8925p2b2/48bXgsjRU1xGYmUHGogs0ryslftpvp10zq8/ElEokk2JACJYho1ycDQKAINTQiToSqYjlLFE91azWJYYmkhKf0bxpFqKA7+r5/B0ZMTwHcmW6HTkzCaG1m4yfVtDRs4NzbZnqlDYlEIgk00kk2mBADaAgF8ErmOR9jGIY7qdwZOCfzHArrC/nVhl/x7K5nCTOFceuYW3vdjhCg+Oh8zLxhKgD5G5o4+PnBbraWSCSS0EAKlCBiII2ggIIQAawF5CXmZczjB9N+wLIjy/jztj9zfvb5/N/k/+v1cRQMMPlmVEnVVG78qbucwccvFnHieL1P2pFIJBJ/Iqd4gom2/nwACBShKCHh9SuE6PZ03zr2Vm4ZcwuGMND6mr6/B3lQ+kN8eiTzr0xi9duVrPrXBq7+mY9qCkkkEomfkCMoQYQYUGHGirtTDnJ6IlDA/Zn0WZwA9CAPSn8Zd9F4kjKslJVqtDY5fdqWRCKR+BopUIKJ4B9w6CUD7g31GUUYKD4cQWlj3g1jAPjvj89eNVkikUiCHSlQgoiB5YMSGgghUPyio3Qw+V6gpI+IIzHNjMMu2LWywOftSSQSia+QAiWYaO8oB4JCCY33IPzmJyN84oPS7HDxk7d3Me83n3LdP9axpbCaa37sroa8+rVCXM7uk8NJJBJJMCIFShDR1lkOiBEUBTnD0xFhoPjAB+Wht3bx5tbjXDQ2FbtucOu/NlLV4uDcqzMB2PTaNq+3KZFIJP5ACpRgZAAIlJ65ngaenjrJ9hcF70fxGIbg/Z2lfGfRCB66dAz//cYMmhw633l5G+PPdxcY3LqmnpZG7ySIk0gkEn8iw4yDCc+Iw8CI4iEk8qC4BYo/hnq8nwdFUcBqVqlqtANQ64ncGRIfDkBCosGJKpV/f/8LosJbSUozkZSbTPLILJKzo7FFyto9EokkeJECJZjw6BL/+UX4ktCY4xGtrShaf8KHe4rhdSdZRVH4xryh/OmTg2w7VktBZSNZ8WH87PKxAFz/yCLqKluoPFpL5b5CKo7WsG1lOY6PqgGICm8lOd1MUm4qySMzSMqOkgUHJRJJ0CAFShDRNnISAgMPPSMEhJarthbFavV5Owq+CTO+d9EIsuLC+Wx/BVOy4/jmOUOJtLp/1oqiEJscTmxyOCNmpAMgDOEWLUdqqNhfSOXRWrZ+UoJjeSUAEeGthKdGkj4iiSF5ye6RFilaJBJJAJACReITRIiMoDSfqMbqB4ECwieJ2hRF4eqpmVw9NbNn26sKsSnhxKaEM2JWhtsyj2ipOHyCHR9/Sk2lTtUxJzs+KgXAHCGITbORkZvAkLwkkoZI0SKRSHyPFChBxMCY2vGgEBIjKHaHHasfpnjCbUWgBKdPekfRUlNUzZS0cIbNvZTaimbKj9ZRuK+C8sI6dqwoZvvyEuBU0ZJMcnYU1nApWiQSifeQAiUIGRg+siqhMIISmZpKS2OTz9tpsWcQFhIfrOJ2HFYV4lIjiEuNYNSsk9NDtRXNlB2p49j+CsqPniJaIk+Kluy8ZJKyo7GGyUuMRCLpG/LqEYyEQj/WDe7ImOB/IxHx8bToLp+3oxjNNL/0C7f6VBS3v5GiuosqurfANG4BltEzfG7LWVGUM+rKjqJl9Gy3aDEMQW25e6TlWNtIy8fFbF92UrTEtY20jEomeUg0FilaJBJJD5BXimAi+AcceoEIiaEgs9mM7+UJsOAncHy3+7kQ7sKQQiAwQAiUmsM4D6zC8v+W+cOas9MLL21VVYhPiyA+7RTRUuaZHtpfQcXROrZ/XMy2jqIlPYyM3Hj39JAULRKJpAvkVSGIGFD6hJBwQfFbojbbRd8463r7+g9wffYPP1hydhREv31lVFUhPj2C+PQIRs85KVpqypo8Iy2VVBTWsX15Mds+PF20ZI9KIWlIFBabvDxJJIMZeQUIQgZKorZQwPBbscDuMIJoRsz7hqiqQkJ6JAnpkYyZ444eMnSDGs9Iy7H9FZQX1ncQLQJLFMSmh5ExXIoWiWQwIn/twUQoDDn0EEWExhSPMARqMIxdGQZBpFD8gqqpJGREkpARyZi5nUVLmyNuRReiJS49jPTceHJGpZCYJUWLRDJQkb/sIGIA6RMIESfZYBlBEaL/UyveIpCno6NoGTvvpGipLj050lJRWM+2ZcVs+6CzaMnITSB7dDJJWdGYrf7IDiyRSHyJFChBRFselNYnbkVo9i4Ui+j6uTj5RDUasSYoqOYe5qQ4Uz6107SFctKeHoyMhJcfZPl/n8MIS0Bpi1rpJYYwELqBoesIQ0cYBgJQVdV9TFVFVTUUVXU/1zT3Os9yVdM8yz2vVa39OaqCqqo4WlpxOVp7bZsvUBuO0PraL/D4z4I4+eEIQ6DEphG25A6f2qAEYf4aVVNJzIwkMfOkaNF1g5rSJsqP1HFsfyUVx+rZuuw4Wz8oBgSWaIhLCyNjREL79JDZIkWLRBJKSIESRLQFT5hmX9+5rpyi0EkxnNrZd3jtWvk3nOFDsU690HNQccp2p3Q+Z+qLepIItpNgEZ2WGyW/JnfMaNSEoRhdRYV00Ql2TFSneESIpmloJjOayYSiukcYDF3HMNzCRdd1hOfR0F0YhuF5rmMYnsf2PwOn04kw7G6xIwSG3Q5VJd28Ud9jHjOPlvxFcKKm/fNsH1DxhCabdvwDfCxQQgVNU0nMjCIxM4qx57iz6Oq6QXWJxxF3fyWVhfVs/fA4W9/vIFrSw8jMTSB7dAopQ2NQ1eAf5ZNIBitSoAQRbR20bdZlfQ67dG18AyN+Aoy90ouW9cGOj/5J7oTJRA+bGFA7usNRV8fb674ItBlocYlEfusPZ92m5Ucf+sUWEQw+OX1A01SSsqJIyopiXJtocZ0ULUUHKikvrGfLgeNseb8YcwRMXJjFpIVDZUI5iSQIkb/KYKKtX+jHTZ03wkS9gYJ7WiLoUZTQ6Y79cLM/0MYTNJNK0pAokoZEMe7ck6Kl7HAdG5cfYPP7x9jy4TGGTIxhzmWjiU+LCLDFEomkDSlQgoi2EZR+DTsHjbOlQNFCoLsLgUgjfxNkLiheRzOpZIyM4ysjZ9JUa2fLisPs+aKUl7duICZTY9YleQyfmIIip38kkoAiBUoQYTjdOU37kwdFCB0lSASKux5PcKMoijskWuJmkPXJEbFWzr12NHOuHMmBjWVsWl7AR0/twRSxi/HnZTDt/BEyjFkiCRDylxcEHN9TydbXd1Je5kJB69cAiBIswkAQGnegITSCIoQKuhM0X1YNDp3z4U1MZo0xczMYPSedsoI6Niw7yLYPS9i+7DjjJ8L4K2YTmxoZaDMlkkGFFCgBpraimXf/soOYCJ2xs5LImTMUVeunwAiKTlegKMEf1qkbBkV231cz9gZCmMDRCGFxvm7Jx8cPXhRFIS03livvmU5jTSuv/uY5DuwZys5tG8jObGbiZVPInJAusz1LJH6gXz3hY489hqIofPe73+20fN26dSxcuJCIiAiio6M599xzaWlp6U9TA5atr+3ArOpc/9hi5tw6hfTcfnY+QZPBVUAIjKCoJhMpZlugzegFwX9OBwqRcTbCEg7w1d8tYsHSPBpbbLz75H5e/uH77Fqe3+4E7nLotDY6MfSeF1mUSCTd0+cRlE2bNvHUU08xYcKETsvXrVvHRRddxIMPPshf//pXTCYTO3bsQFWDYNohgBzeUsrej/bitOsMnzuMkfOGYLGZKDlcT1KiisnsrdGGIBEoQgSJL0w3OJ1Y1FAZSBS+z8/r58ETYQicJY0IQ2DJjArKaUGTRWPMOZmMnpdBycFadnyQz+q3K1n99mekZWmUFunt246aFo3qbEQza4y9cCLhcTbCIi2nHVMIgctpdEoed3xfNU6HQXxaBDFJYX55bxJJMNOnK3NjYyNLly7l6aef5pe//GWndffddx/f+c53+NGPftS+LC8vr39Whji7Vhxi9RvHiItwYLGqrHnzKGvePIpJMXAJMzOvGeG9xgQEw122CJqRnLOjOxwo/Z1S8xOKqiJcus8/XX99aobdRdV/duM4Wg+AOSOSpG+MQw33pY9N7+h4LhRFIWNkHBkjz6XsUA37Vh9g96bO04P7NteTENfCiZow8jdvBiAivIUJl4xmyqJhgPu38dZfNlK6t5HU3CiqyxoRBjibTx7n6h9OIXVYrI/fnUQS3PRJoNx9991ccsklLF68uJNAqaioYMOGDSxdupQ5c+ZQUFDAqFGj+NWvfsW8efO6PJbdbsdut7e/rq+v74tJQUtrk5MNbxeQlWXlsh9fiKIoNNa0cmRLKXXHqojPSSB3VqbX2hNCR9WCw/cjFEZQjNbW9gy1wY8LxRIeaCO8RsOaYpwljSR+fRxoClVP51P9+kESbx0TaNPaOdOAUmpuHKm5M5l3q45mUik9UI2j2UnWuGQ0s8rx3eWsf3Mvw6Zlsendfax77ShJabFk5MWy+4tiSvc2AQplBQ1kjovCGmEmITWKUTMyef7HX/LeE9uxRZlobXYwZm4GUxYPbR+Jaayxo2oK4dGnj8xIJAOJXguUV155ha1bt7Jp06bT1h0+fBiAn//85/z+979n0qRJPP/88yxatIhdu3YxYsTpIwWPPvooDz/8cB9MDz5K9lex6eXtmCwqGRMzyZiQxid/20irbubcb85od6yLjLMxfvFQYKj3jTAMjK2voo+agpYxyvvH7ylC0FCwlfC04YGzoQcIBC2tLRQu+6DT8lOdIE99bRgGhmEghIHQncSpJwgPO+nLorRWg6ohzNHtLbU/9nYaxRMGbRLVKNue65CoxOh86NPaEJ32B4FTFxxzxSMske15d4qrGkiJi0A3DI6XVzImIaWXBvYNZ0kjlpwYbCNP+l217jnhl7bbqDm2l6qC7e2v3Wfk5Gfd6nCddf+2qdn0vIROyzPHpnDNWPd51L/8JRsrb+Hdv2zvtM2df5mPEJxW2HDu9UNZ+7/DOJrdn+/25cVs//g4485Np7mphcOba0AopOaFs+CGccSnyegiycCkVwKlqKiIe++9lxUrVmCzne5YaBjuH9Sdd97JbbfdBsDkyZNZuXIl//73v3n00UdP2+fBBx/ke9/7Xvvr+vp6srKyevUmgoH85fv5/K0iYiJ0TJqLL987hnjvOKAwZko0sSn+ufO1XvtzHP/9LvYPnyL89j/6pc2uCL/4IeLfuhrmXdvjfQxDcGRHJXUVLWSOiiM5O7r7nfpJWFIyQ4bmcmj1pyf78zMoiE61gjwFEFVFpaWlnBhRxKQhae3rNVcpQrFgaG0d18lOzz0Ld+pESvcTK+bUiXD4087bth/n1Mcu1ilQXuNgfX0WI7LTQVFQgLITdmKEDU1RyM1IJGv83G5t8QbmtAgavyihtaAWxeQexbJ2ECv+4IvlbxCuuYiOjW9f1vGTmDl1Ur/biBwWw8zUHZjHfoWaiiaSM2JJHxGH6QzFCyctGMqY2VkoqoLJpFJZ1MCyp3ewa1UppjBB+phIYuIjObS1nJcf3sDQqfHMuDiXxMwowO3XU1pQhy3CTHy6zIwrCV16JVC2bNlCRUUFU6ZMaV+m6zpr1qzhiSeeYP/+/QCMGdN5iHb06NEcO3asy2NarVasVmtv7Q4aHK0uDm8pZc3bxaQkKVz18PmomorLoVN2pA5ni5PsCcl+s8eUMx7niIWIhkq/tdkV8RMXU/ruMNK63xRwd/7Ln8rnyI4qzFaNdW8VcN7SPMaek+FTOzWrlfm//E2/jlH8yXMc37ebiP/7rZes8h3K1hVk7trEjOvvb182PUC2RJ2bSevBWqqezgfAnBpO/HUj/WqDpsDUuYuIHXWOz9owZU8jqyaflPNyerxPx+RwydnR3PrIPOqrWoiMs6F5xNy5147io2d3cGRLDUe2bMIWpxCfFkbl0WaczaCogqu+P43GGjsFO0vIHp1M7tQULzrkSyS+pVcCZdGiReTn53dadttttzFq1CgeeOABhg0bRnp6ertQaePAgQNcfPHF/bc2CKivaqGmrJmGsnr2rDhAdZ2CjonYMAdTr5rQnsPEZNHIzIvv5mg+QlURXVUQDmJKDtZyZEcVF905jmETk3jvr9tZ9eJ+RkxPCfpMnsLlQNWC28Y2VEUhWEokqTYTyd+eiONYPRhgyY4OSHkEX58OBRCif+9LURRikjqPwposGktun8yqV3ejYqKypIba8hYyRseQlp3A+rcLeOO3WzwHEBzaUM3KZ/eROzOeyQuHkpwd0y+bJBJf06uralRUFOPGjeu0LCIigoSEhPblP/jBD/jZz37GxIkTmTRpEs899xz79u3j9ddf957VAaC1ycmW13eyfV1d+7K0JJWpi9MYtTCXqPjgyaUhFBWM0BIojTVuR+msUfEoqoLN4xDYVGvHkhrcnb8hRP/qJ/kRRVUwgkWh4LbHmjOwO0pFAeGj2ChFUVhww7gu140/L4u6imY0k0pkvI3q0kZWPLeDQxuqObShmqRhYWSPTWT4xNT26SGJJJjw+pX/u9/9Lq2trdx3331UV1czceJEVqxYwfDhwe0seTYqCut597fr0HWFtAQYsSCXkXOysAZROGRHFFULuRGUtNwYVE3hsxf2MWxyEpXHGkjMiiQuNfjn0A3DCJnMomooVW/2A4qC74dQxJm8mnyL2aJ1Eh4p2THc/NNzcbS6WPFsPke311B5uIjNHxzj6785h7AoGRUkCS76LVBWrVp12rIf/ehHnfKghCoVR2vZ+r/tFBw20BSNGx6e4zdn136hqiD07rcLIqITwlh82xhWv7yfQ1sqSMiI5IJvjA20WT0jNFK+AO477sOVrbz22mudlosuCiZ2XHbq+rbXQohOz8+2rK/r2v7cUVMnH4HTslh3ZN++faxbt46wsDCsVis2mw2LxYKmae1/RXU6M3ysHtQg+4JYbCYu+dZkhCF48p5PicsIwxoe3KOUksGJ/FaegfLDtbz9241YzQYzFmUw8dLRWMJC5HQpWofQ0u4xDMHHe8rZV1bPpKxY5o9MCsiIwIhpKQyfnISjRccaYQqZUQlQQqZ8TYTNzFD1OJbkxaeta4tMEkJ0OvenLmvb7kyv27JGn/q64/JT/05drqpqp+Umk6nTn6ZpPPXUU2d9rwcOHMDpdDJixAhaWlpoaWmhubm5PURc13WaHODSfSzmfTjFcyquOjt17x/GUdSAOS2C2EuHYUroOiutoiqExao0VtvZtLyAyQuHhs41TjIokN/GLmiqs/Pe7zcQG6vylZ8v9pqTZn5lPu8UvINFs3DtyGsZGuODPCgAigpGzy+6P3pzJ//bfJz4CAt/+uQg35o/nB9d7IUcKn3otFVNxRYZKonTOhIaCkV3ORkSYyJv/vxAm9JvNE1D13W0MyQmDA8PJykp6YxJIgGWP/MIJh9nElbAL18PYQhOPLsbo9lJ2KRkWvKrqPrPblLum3LGbMlTLxzKF/8rYPN7RRzeWc6ND575XEkk/kYKlC7I/2AfdsPMTT+e5zVxsqF0A3euuJP0yHTsLjtvHHiDly99mWExw7xy/E70YmK9oLKR/20+zq++Mo6lM7N5+L3d/GN1AddMzSA3uZ+OcyEzAtJPQuh9Ol3OM3booUZYWBh/+MMfTluuqipms5mmpiaGDBnS/YF8/PkpZ8ys411clc04S5tI/Po4bCPjsGZFceKFvTSuLyVqbtfh+sMnprF52VFaagxyxvovHYJE0hOkQDmFvauOsPPzMpLivJtK+rndzzE2YSzPXfwcDt3BzJdmcsuHt7D2xrVea6MdVaWnAqWi3h09Mz3HHRKdGef2sckvruu/QBk0+MPT0ju4nC60EKk91B133333acsMw8But9PQ0EBjYyOJiYkBsKwzJ6qqUKqr8V5Bi65RPPlN9EYHAEarOwuudgbn15KCGt7/2zYMQ3Djz2bKjLSSoEMKlA6UHKrh01eOkJVlY+Fds7x67CZnEykRKZhUE5rivpDUO3xUd6gXYcbjM2OICTPz0Nu7uH5aFm9tO05GbBiXTUj3giGh0Wn3G0Xplc9PINGddhRt4EZrqKpKWFgYYWFhJCd3PyLgzlHiW5sSExNQ1FrfNgKY4m2EjU2g5o2DNG8ux36sAWtuLGHjTxdp2z87ytr/FRCZaOKq+2YGVZoEiaSNgXEr5SWsYe6w4VELhhEZ593stouzF/NJ4Sc8tvExHlr7EAB/XfhXr7Zxkp5/rJFWE/+8ZSplda3c/9oO7E6Dp26Z6vN5eUlgMHQniik4w+MHKv6a4gGIv2EUMRfkoEaYiV6YRcKtY7p0Nl/3VgEIhUvunCrFiSRokSMoHTi6/ggAjiZ7N1v2nqWjl9LgaODNg29iVs38ZNZPOC/rPK+3A4CqQC/yoMwclsDqH5xHs0Mn3KKFUPRMkBA6MzwYTjuKKn/2bfjloxMCf90LKmaVqPndTybNvTqXL/53iFd/uZHF3xhF3nT3iKmuG9SUNtFU20rZ4RPUVzYy55rxRMSEbjkSSegir1QeqkubWL+iggmz4hm72PtJ5VRF5a5Jd3HXpLu8fuxTURS11+PWiqIQYfXy1yFEOu3+o/rxHrmfGDpCChQ/YwSdI/WE+dmMmZ3Ji79Yyyf/3svmjw4Rm2yj/GA9LQ1t4eAGQqg012/mivv8U0BSIumIHMf3cGDNYTQM5iydGPojCIoCBEEm2RA/jT0mhL4vmmIETS2e4MAf8b++b6IvmCwaNz40hykXuysnF+ZX4HQ0MOOyLJY+PIs7n1gIwPH9dg5vLwfcxVF13QiqcgmSgcugv5USQrDh5R1sXV3FiNHhaOYBoNnU3iVqk3gBL5zv93aU8OqmIiwmla/PHcq8Ed6PQFFVDUN+N9pR/JBjT0FgKMF5XbHYTMy+fCSzLx/Je/96ipjEJKZfMqJ9/YzL0tm24jjL/rEbVduJobeFqAtiU1TShscybckoohO7TgYnkfSHQStQDN2g5FAtXz67hcoajcnnJDLrxgmBNss79GGKxzeEzshCf/DGAMp7O0q45+VtnDMikZpmB7f+ewOvfWs2U7O9WxFb1TSErzOn9gK90UH9ymO4ypux5EQTdV4WqsXPeVp8XovHIBR+C4aho56SI2f6JaOYtiSP/euLqS6tIzohiub6FsoO19Bwoom9X9aw98t13PXkgtAfeZYEHYNOoAgh2PHhATZ9WIhDNxFlM7j02xPInpjileO/9etf43A4UD3pulVFQfM8tv2hKCgooICiqii4/Ubcq1Q8C9xpv1FA7ZAS3HPc6TfeiDXqDHlKQijsVeLmlU3HOGdEIs9/fQaGgOE//pCrn1zH0ccu8Wo7imZCGC6vHrOvCF1Q9cwu9Ho71mExNH5ejLOsmcRbx/jNBqXDf19ilO2ifNty9+9cVdw3ESgedduh/bbXnkfhuU4IA+odZjRrBFpbun+zCZPJ4nk0YzKb0Exmd50hU+8v7YZunCZQ3CYpjJqdCV1kctm1ppDVLxWw4l9bmH/TxKAtoCoJTQadQDm2u4q17xWTFK8w+5ZJZOTFoareu0BVNDRwzTe/iXC50J1OdKcLw+XEpevouu6ubGoYCEO4Kw4LgdB197B7+zpPMTTPn2EIEO5lwjDYumULww8fJm3ixK6NUHqeqE3Sf9yF6/r3HWo7hOJjcamoGsFSz9hRWI+zrImkb0/Emh1N3UdHafisCEdRA5Ys/yUJ9LWDc3TePKqLttCy423g5O/65G/U/agIgUC4Px/RttxdxaemsJDtNWmI5Fx3sURDb79WGHrn18IwevSeFBRUkwnNbMZksVJXfIz04bm9em9jzxlCU20zW5Yf5+DmNUTGGpx743iGTkzt1XEkkq4YdALl8BdHsGkOrv3VhT4ZkjQLSBju/SigjhzauxfT2dKVq2qvwowl/UPohvuuuB/cMGMI33l5G7f+eyNNdheqAv+7c7aXLDyJIHi+G20ViRXNc+48D8LfDpg+bi46ayzRt/2zX8dwvPVXJteeYMJtP/eKTUIIXC4X9pZmWpqaaG1uorW5meyRvavBpSgKMy8fzbhzh3FwczFrXz/Kh0/u4fY/JsrCg5J+M+i+QaWHaklNUX04X+r7i6shRHtl2C6RIyh+RRg6qto/v4nLJ6YjhODVTUVEWk08e9sMpuV41/8EAFVDCRKBYs2OxpQYxonn92AdGUfLriqsI2KxZkf7zYb8CoOshma8M8HrO9zVpL3naKsoCmazGbM5hsjomH4fLyLWyqTFw4iMtfLRM/t47sefcd2P5xKTFO4FayWDlUElUHSnQV2jwphFPqoiDP4LOT2rQJE+KP7EMAyUs30ePeSKSRlcManrom7eQwkagaKYVBK/OZ76j47iLG0iYkoK0Rdk+9WGCckKMdERfm2zTwjDc+MRvNRWNFN88ASKCo4Wjf0biphxaV6gzZKEMINKoBzZWYmBxpCJaYE2pV8IOLsQUrWgGcYfDAhD7/cUj98Isu+GKdZK/PWB68QUlx1cjoC132MMI+ijZN7905c0VKskZ5sYd14uuVOkH4qkfwwqgbJzxV6gkbf/+kv3gjbHRAAUdxRNW3QNHd0elfbninJy+anRN/66fuhOJwXP/JOS8PAuXTPD6g+TFrGL4hfuR1HaIgEUFEVtc8dzL1fU9ogi0R494LlLUzo+V4G26CLVI44802SKiqKZ3FNOqtb+XNE0DGcz7376qedYJ/+Ujq+Fx0nRcDsIto/8tDn6CeFxGAYQJ/0T2vdv24/TOt6299q+fRudTpriGT4/NZLilEkypeO3ofPy5qNVjIwLjegFgUpQJPELFuqLobUu0FZ0i0AEfUJAk0UFxWDakjHSSVbiFQaVQLELE9Fpsdzys0cB2qNihGGAYXi84w3Q9ZPr2vo+YXg6TdzbgDv6xjAQLheGriN0HVtM/+dzu6M1JgpnhI24pJPVWjt2pi6RTnXUOJSI8HZHRDDao4baRQGisxBojyBwv1eEy71NW8ff8bFdOBgYho5LGO406u2RBDpvxC7EVlPjFgDCUzStPTrJ6Bi64hEudHoNnBQ0nnDrk/JAoAjhEUx0Cs9U4JQpLnH6SeqwTDltWZsI6rjPyZ2V9l3dTw5GJGHOTMC79a99hKq6z5vETcIwRHhCoK3onlNFdBByxX1zeffP61j+z51c9X0bKUNjA22SJMQZVAIlIT2Kgs1VCEOgtOUW0TTwRMT4OT1UnxEWC8mLFzNi0pRAm3JWlr+5nBVXXRRoM3zO21s+xuVyBtqMHqIGjQ9KcBDcnX4bbk0Z3LZGxFj5yvfm8vIvVvP6b7Yy+yuZTLlwZKDNkoQwwe115WU0c9vddqAt6R+GEGhnCzOW+BUhhDsBXygQLHWagoQuJvN6RHl9K1/7z0ZGPrSM8/+wmi8PVXnbtFMQwT7DA4At0sxNP59PWBTs/Kww0OZIQpxBJVBUVXE7w4fCL/1sCAO1D5kiJb4h9ASKpJ0+Brzd+8o29pU28MML80iMtPKN5zZT0dDqffs8uGdDQ+Ozc7TqtDbpxKbIEGNJ/xhUvVxSZgx7XBU899NVJA2JIjUnnsT0aGrKGzm0o4SmWgcjp6YxY0kuqha82k0Y3eRBkfgVA0JIoARLnaYgopfno6HVyfrD1fzumglcOy2Lq6dkMvmRFfz4zXye+ep0XxkZ1AO/9SdaeP+v64hPi0AIK8LQWPTVqYE2SxLiDCqBMnauu5bE3g1FlByo48iWWhBuT8iIRI2wKDNbPihi9xfFLLhpLMMmJp/1eIHCEKLLmhmSwCCE8Gq5BF/SakBReRkv/O/N09Z11U23O1l3FdnUvs2ZjnAyqf6+plZGRdpOi4Byb3XKf89G150zl1EpSWd8L95A6UO3bzVphJk1DlY0AnCgvAHA64UdOxHkIyjH952gpgxqypqAJlJyTETF2wJtliTEGVQCRVEUxs3LYty8LAB03aCp1o413IzVk5a57Egtn7yQz7IndzFuUQrzrx0bSJO7RhioWmiEtQ4GDARKiMyW2qNiaMrIZuGsGUCHkPlOYoHOz0XnBQpn3ra9D+0wKqGgUOV0kmA2tR/M6FCKxmhfJtp3/Wz7DrYeO+5zgQIgeumTYzGp3L1gOL//+AAr9pRzvKaZqdlx3H6O7xJAiracCEFK3ox0yg9XsWftCXLGR3LJ3TMDbZJkADCoBMqpaJpKdEJYp2WpQ2NZ+tA8/vPj1ZQdrQ2MYd0gDBHUU1BtBPENn1cp003E9jPVvb/QFIXo8DDmDDm9Mm0wsedoIa0uP1Rd9uTi6S13L8glLzWatYeqyEkI5/rpQzD58jcphFeyFfsKzayy4JZJtDZt4Wh+daDNkQwQBrVAOROKomAOU2motNNUayci1hpokzohkFM8wUS9UFGNEFFjamiUQbBZLdQ5fZ/hta9RPIqicP6YFM4f458qPkKEhp9TzoRUDm+vo+p4A4mZ/qtILRmYBK8kDzAX3TYJ3SF4+VdfYm/xw51cLxCGgWaWUzzBwmiLTha+i+DwJu6pqOAXKBE2G62t9kCbETS4J3iC/3Mb6vHb+/yV7YE1RDIgkALlDCRlRXP9j2fjaDFY9szWQJvTCcMQmM2WQJsRNBiGi8rKFRwvfomWlmK/t68pSshkFlEU1eMAEtxYLRZcjlBJfud7hGGghMA04olit8Pw8KlDAmyJZCAgp3jOQmxyOPOuzeXzlwv45IWdzLpkJJFxgfdMd0/xeF9blhysZf/6UjSzxrj5GcSn9a/Kqz+6QcNwsG3716it3YCiaCiKiYkTniY+fq4fWnejAiFQbg7A48cQ/HJKUVUaCg7w6qu1OJ1O9LayEh2mp1TVXQ9KVVVcLheNjY0kJia6M0R7/jpuoygKZrMZi8XS/lfSaBBTVIDJZPYc3+hQAkMghEFs+nCiM0YE8GyAYjgRamRAbeiOhupWlj21FYtNMGZecPs4SUIDKVC6YcL8bGoqGtn1WRn7v6hk4oXpzPvK6MAaJfoWHnk2Cned4P2/7SAuJRynXWffulKufXAacanBXYq+omI5tbUbmDL5RaKjJ7Bu/fls234rixYW+M0GrddxIIFDITTyoKgWC9UJyaSnp2O1WjGZTGia1p7/RwjRLloMw8DpdNLc3Ex4eHj7MiFEp0fDMHC5XDQ1NVFTU4PL5cJpiaOirIQTlWUobQVDFdVT9kmhqakJh2sVV9zzWEDPhyJ0hBqcl2tDN/j81V3sWlMFqFx6z3hM5uAf7ekKXTdorjv9duOk+49y+rIuLsUtDU6s4SY0k3qyTBgKqknBYgvOzzEYkWeqB8y/diyzL81jxfP57PykhDmX5511BEMIQeveauxH6zAnhhM+JRnF5L0RD1+U5dj+yTHSc2O58r7JuJwG/7x3NW/+fivf+P05fT+oH/rBltYiTKYYYmNnniwq6Gc0BfQgDgHtiDtfS/ALFLPJjEjP4pxz5gTUjqoDm9i66v2A2gCgOx2YzcHlrA/gaHXxv19/Tl2FYNy5icy4fBRhkaE5/exy6vzr0Y24Slp82o5leBTzF2eTOzEpZPInBQopUHqIJcxEXGo4hfnVKN18qeo/OUbDymNocVYaa+0076oi8Wtju92vV3jZo99p14lOsKGoirtsOtDa2D8fAH8EHcTGTOew6w8UFPyWmJjJCOEkLta/dYU1RCi4dQCefCchUCxQ7Vv0r9dxtjZiMgf+Mmk47WhBKFCO76uhrkKw+GujyJuVHmhz+sV7L+/DUd7KBV8fQ1ik+exF0E8dhezwUtcNju2uJmlIFOHRlvb1AkFdnZ0Nnxez4qldfBRtYtw5Gcw6L4uwqNAUdb4m8L+8EMJp1xG6Ow+JonXd+xoOnYZVRUQtyCLmwhxadp/gxH/30Ly5nIgZqV6zxdv1hHKnJrP2jUNYI/bT0uAWJpd9Z6JX2/AFcXEzGD7sfg4f+Svi2D+JihrLmDG/86sNAiUkIiwAUEKjmnGweMo4W1swB0HEnO5yoVrDut/QzyRnR6EoBgXbjoW0QNm1qYySL8uZfl0ueV64Tg+ffOYs5FPOy6L8aB2frihk1/Jj7FpWSMLEBBaen03K0JjQrxXnRaRA6SHVpY0c2FiGJUI560iIsOugC8zpbt8Ns6dglv1InRcFivc7w4kLs3DadfZ+WYrJrLLoq6MZMiahX8f0l6tDTs5dZGbeistVj9Wa5vcfuI77jj8UUBQtNHxQACMIps2c9mZMpsDf3RpOJ5o58A76pyIECKFSWdjU/baGoORQLeHRlqDybautaObT/+4jYXw8Mxdk+aXNlJwYbrx9Aq2NTjasOc7O1cd547dbUdLCmL1wCONnpmKyhKYfjzeRAqUH1JQ18eqjG7CEqVz5neln7QDVSDPmjEjqlh3FaHTSvLMKxaoRc+kwr9rkbSdZRVWYfslQpl/iu3TdvsRkisRk6n2UgxCCvfs/R+hOdwiuoroTYnmeu6NBPI+q5j7vioKiqqjCnZuipbaY+NZq2MdJF5i2zOSdxIA4ZR1guEB3uB8NF+hOMByge14bTtB193PRcRvd81p0WKeDYeAZ5vNM5XRIka6oxDlaqXIEv0AJltBtl9NJbV0tJdtWAO7IINr+2r4LigKoJ5PgCdE+BSCEwNHSglm3Y9I0FM2EqmoomoaqmTq8NqFq7uXu56b29Yqq4bI3oQtwtDS715k01ACHHdtbXLz7p/UAzF969tHW0oIaPn5mC4017jw8kxanMPeacX6w8uzoToNX/rEDNVzjmq+P8/vNjS3SzPwlQznnohyO5Fex6pNCvnxxP5+/cZDhs9M4Z9EQohODb+TMX0iB0g1Hd1Xy0TP5KAos/ek8bBFnH+5VFIWEpaOpfm0/te8WYEoMI+HWMWjd7DcQaa6rDbQJ3VLTXEf8O3dweOzNCCFQMDx5QjwdvGh7Ljx/7uWKMBCKgkAh2eVgTOMhKP7w5IE7lk7pKFI6+agKUE2gaKC2/ZlOWdb2WnU/am3rTKBawdxhXdv2besV9ZQ2DRy1pTirK3x5Sr1CsEzxpIyYQvGxI+zfsfHkQiHctXEEuP+dfO7+2JX2qocKsG9fCcmanbQ4W6eIorZwZsMQnuWiw3LhWW5gCEFTi87OF19FvPA/Tyh0W9tuXHY72RMmc/n9P/bXqWHNK3uprTCISbaRMz7xjNsd3FzCx8/sISJGcMld49n9xRG2f1JBbfk6Lrl7tt/s7YoPXtuPs6yFa344tb0eWyBQVYXhE5MYPjGJ2opmVn9SyOEvSzmyqpiIvBgWXJBD9uj4QTf9IwXKWWiud/DB33YSlWzhsrumdCtO2jDF20i+c6LbV8UXY//BfwMMQHhsbKBN6B5hcDxpMnMufSjQlviFwr2f4zJWBNqMbuljiRyvE5uVx8Kv9a/Tr/jjbxk2dQaTzz3PO0Z1wc6Vy9m/7gufHf9UWhodHNhQCUBdRSv71hWza/VBnHYDp10nLNpMeJSVploHlUU6qcNsXHn/HDRNJXt8Iqte2MWetZUc21vFkNFnFje+ZNsXxRStKWXKV4aRlhMTEBu6IjY5nCtuGo3z6pFsX1fCxk+P8cFfdiDiLUxdmMXUuRlYAiim/MngeJd9pC2aZcycDOJSej9n6hNx0n7sEEgCHAw9TDcoQV7G3tu46ooQUcHvzGiIgZPm2jAMn9fOcra2YrL4L8rHFm4mZ3w49VVOqkudrHxuP6pmEJ+mERlvpeGEnboKB0LAvOtGMv687PaQWkVRmHPNaPasreTojmK/CxRDN/jg1f0cW1NK8vQk5lyQ7df2e4rZqjH9vCymzc+k+GAtn358lC1vFLD5ncOkT0tmwfk5xKcHjy+PL5AC5Swc2loGQgno0F9XhEC/7yYk+n2BCA1DvYJub0K1Rvvk2ELoVFR+RHPTYWJjZxAXN6PvxyJEvj49QBi6nwSK/6aRFVXhkrvd4fwniuspPnCC0XOHYO6hY+fyf2wADPJm+VcctDQ4eOnv22k52sjkq4Yx5/zsoJ82URSFzJFx3DoyjsYaO2s/LeTA2lJeXleOZWgk556fzYiJSSFR4b63BFfPGyToLoPPXt7F/rVVZIyNZNw8/3h2S/yPIgRGkF+gvIlLCGyK9yWuEIL8Xd+hsnI5JlMsh4/8kdzhPyQ7+84+Hc9AoIRAtFFPEP4YQXHYMQWoPldCRjQJGT0XvZs/OMDx/XamXJBOSk6s7ww7hdKjdbz+9x0Ip+DyeyeSM6p/UYqBIDLOyoVXj2Tx5bns2VLG2k+O8ck/d/NxtIlx52Ywa/7AyqkiBcopHNhcyhdv7KOl1mDapUOYcUluECrs0Lhwt6gaKwuLsagKJkXBpIBFVdt9NjtmD2k7xUaHTqmL+BePg2JnOvZjRg86tY5HaGmqxhwqWda8geKbjC319TuorFzOuLF/Jjn5Enbt/g6HCn5LaupVWK1JvT6eIUQQ/u76hjBEe4p+X6G7nGim4L+cb1l+gA3vHWfEtGhmXemfkiFCCDasKmLTa4cwp4ax9P8mExUffCHbvUEzq4yflc74WemUH63nsxVH2bXsGLuWHSNhYjyLLsghJYj8avpK8H+j/Uhrk5MVz+zBFqNxzQPTgvoDDoUUyUPKjvPmwTB0FFyAC3dKeAOBelrErTvdmdJhcP9M77C9BIZy+rIzbXsmrPYavtlY3/2bGSCcFvnsJeyOcgBiY91h+BaL26+gpaWwbwLFEAPIB0X3uXgwdB1FC+7LuaPFxcZ3C8kZH80F35zmlzZ1p8Hb/91D2cYKMuekcPmNo9HMA+Wb5SYlJ5obbp9AS6ODjWuOs3NVMa9v3YKaEc6884cwZloqmhdLrfiT4P5G+xmLTcMcoWCL0oJanIQK0yoK+d6dtwXajLPSWn2cskPBENDqHxQfjaDExkxFVcPYu+/HpCRfSk3NOiIiRhATM7VPxzOECJnkd93hjykeQzeC3gdh/bsHMAyNc66f4Jf2mursvPjXbdhLmpm9dCTTzhnYFZbDIi3MXzKMcy4ayqEdlaz++Chrnt3HZ68dZNS8dOYuHEJETPCVSzgbUqB0QNVULGEa9mY90KZI/IUYXE6yCgpCeP/7bbEkMn7cX9m37/9x4sQqIiPHMG7sH/s8TdOeT2QAIITweVI1YehoJv93PkIIyo/WU1fRQlpuDNEJXScVczp08j8rw2JT/JJ4rLigljf+vgMUhavvn0LG8FiftxksqKrCyMnJjJycTHVJE5+uOML+T4+zf0URcePiWXRhDqnDQiOlvhQop9BS52L0XO/VzPEF7jvg4P9yhQIKp/u0DGhUDcXwzYhRYuIC5s79Al1v7lNW347oYuDIRuGnKR5fj9J0xeqX9rP78xIAVE3hgm+MZfiU0+vQfPG/3QBcdIdv63vVlDXx6UdHKdlQji0jgqX/NynkRg28SXx6BNd8dRz2a51s/ryYbZ8V8ebvtoJF5foHp5GY1r/fqa+RAuUUwmI0ygtrA21Gt4SC+g0FFE/Gz0GDoiEMh+8Or6j9Fifguykeo9mJYlZRzP7rzIUhfC9QDMPvuZHKj9Sz+/MSzr1hJCNnpPDB33ey/J+7uPMv8zvVkXG0uNjzRRW2CJW0XO9PnQshOLa3mpXLj9ByoB49XGP0hUNYuGTYgPM36SvWcDNzL8whMTmcT57aBQ6DhjoHiWmBtuzsSIHSAd1poDjt1B8/wdE3fhZoc85Inj2f3Y/8HE0zgaqcrA/TsU6Ip16Mu/89ZbmierJgKe1V7hRUdz+tuNN0i4IjKCOGe4bZ27ZT2kuQOF06J5KSUaIiUDUNTdVQNBVNNaFqKpqqhUJNOp85jfYWIQR7SuuxuwwmZMRg8pU/gaohnME/hWkI7zrJ6k1Oql/eh/1QLWgK0QuyiFo0xC9C3zAMGmprqCotxWKzER0X5/U2RABGUGrL3QUCR81Ow2zViE4Io/RQHfVVrZ0SiO3f4B5hmb90tFcL4BmGYPvaYtatKIQKOyTbmHNznrvQnh8FaCjQWNPKWy/spX53DWG5UVz91bHEJIUH2qxukQKlAwWbimisMzN7fgvm+JxAm3NGFvBvjqcvBJPZXZSsrTiZ8NSREcLT6brrerhry4j2dYbhrrjcXk+krYcWxsnXVVWIBM+F1DhZ+MyzIc179lOVnISYOuVkbRHDwBCeR8Ng4oTxfj0vfUEBRIBHo1qdOrc/v5nPD1YBkJcSxX+/OYPkKO+HQmqqhku4vH5cb+NO8Ou9z6XuwyM4SxqJu3YkrsoW6j85hjkzirBR8V5r40wMnTiZz197CQQ0lJdw/39e8XobkQmJbHn/LfJXfuReoCioqoZmMqGZzWgmE8OnzWTudTd7rc3knGhQYN1bBeROS6bqeANmq0Zs6smOr76qhTWvHCQyTiF7rHczxq7/9BjbXi8gLC+axTeOJmtUnBxZPgXDEKxbUciW94+AWWXB10YzbmZqyJwnKVA60FzdAEDKpAvJGN370Eh/0bLicXK/fjuKNXBzq/l//SsjbTbGfjW4o3S6Q2kv9BY4XlhfyIbD1fzzlqnERVi49h/ruPfl7bx8xyyvt6WqGsII/hEU3csjKPaCWsKnpxIxNQWAhlVFnHh2N5mPnePFVrpm0bU3sujaGwF44t6+Ja7rjnNv+hrn3vS19te6y4mjpYXWpkZaGuopO3SA7R994FWBEpcawbxrR/DlG4fIX3Wc8BgLV3x3cqcUCNYIMyiCUbMzMVu9O6qxa2s5luFRfP0+/4QshxplR+t469k96GUtZM5O4ZJrR2IND62itVKgdGD0wjz2ry9m9X82ctNvLwm0OWdGCAhwUiYRgDlvXxHoGZ7dJfWMz4zhgrEnnbPXHT7hk7YU1YyhB/8IiiG86xmkxVpxHKnDcOjo1a0AhE8+3ZnT5/hpPlEzmQmLMhMWFU1cajouhxOTxfsZRicuzCJvZiqNNXbiUsNPy7dhDTMRFa+w+cNiknPiGDrBO+fc0erCfrSRqVcO98rxBhKOFhcfvnGA42vLUJNtXPXDKaQPiw20WX1CCpQOWMPNjFs0klWvHsHl1IN4HlNAgMWB0AeGQAmGqrmjUqP4IL+UNQcqiQt3dyITs2J90pZmsoDu9MmxvYnbSdZ7EiXmwhyq/r2Lkl+sA11gTg0n9spcrx0/2HG2NKOZfXP3bIswn7XS+5X3zWHZPzby4d93kTREY85VY8kc1b/pnmP7alANGDMxeEe6/Y0Qgj2by/n01QPQqjPx8qHMuyA76PPjnA0pUE7BZHN3EE57MAuUwEfxCGEEXCR5AyUIFMots7NZua+CW/+9EYChiRE8dXPfEpx1h6KZwQh+gSK8PIJiHRpDyn1Tadl7AjXMRNi4RFQvOmz2mAD9bu0tzQGr1ROdGMZ1Pz6XnauOsGVZAe/8aTuX/t8Essf1fTRl6/ZyRKyZmGTf51QJBeqrWnjj+d00H6gnelQsV906JuTT+YMUKKeROMQdBld2qIahk1ICbM0ZEIKW9/+OZeblaEkByo5oGDQePoy9sRFrZHDH0p8NBQVNBLbDDreYeOX2WWwrqsXu0pmWHY+ll6mpnQU70EsOuV8oJ8vagwKK51iqQlTxNmpry9i7fadnT6V9Xdu+7ZFfdDxOx3Wcvm2n/Tqs6+IY7kiyk8dRcEegqZ59FFWhseoE1poaagsLT0an4Q5jbjtsp+Wq6nEMVQlP7Pru3BRvI2puRrfnssXpPGmL569jLR1FOeU9hQCO5mafTPH0FEVVmLhwGOPm5/D0vZ+y5pVd3PTweWh9uLsXQlC+t4aMsfEh9Rn4AmEIvlxRyNb3jkCYxuI7xjJ6SpD2W31ACpRTsIS5T8m+lbuCV6DMvgux/mkcNUcJu+W3ATEhY/Fijv74xxx58y1G3XpLQGzwCmFxJLQeDbQVqKrC1Oy+h5+6nr4OIzoXNE8nJDyRW+4X7ctihYuj9hz2F77TYTkd9jllX8+D0lak0bON0sU2iNPba3upCHHaNuKUbdyv3ZFkEbrOOY317Htd7/J4nHY89xHNRwvJ/tczJI0Zc5azdWYKTtQwd2chE1ob6HgGO75N5ZTlvWFKZBw/fehHnRcKcdrIilpTxdCLruCrl13Wx5Y6ozsdlBzYxwsP3ofJYsFksWC22Vh8+91ERMd6pY2eoGkqC24ZxSf/2cfzD65i1OxUUoYmkZ4biy2yZ1NQteXNqHVOJk8O0uuzn6ivauHVZ/JxHG1kyLxULr5mJBbbwOrSB9a76QeGIchfvpcNHxQRbjOYevXsQJt0RsKuuIem+hpw1QbMhqTJkylevNjdoYQy1kiazAnEBtqOfiJUG2H3vIAa1b3Ime8HewLFhm99G8PR90R0DsNggbORly/2UXRPD4/75qpVVFZVea3ZyRddRuqIPOxNzdhbmnA0N7P+zVeoKChg6GTfTCeeibyZmTTVtrDjkyNsX1GMYZQBAotNR1EhKt5EXGoUyTmJJGbFEpscTkSspX20ZOf2CgxNITPP+/lkQgEhBJtWH2f9G4dQwkxcdu9EckYnBNosnyAFCtDS6OD9335GRYWJ8dOjmHnTDKxhwX1qFJMJ7IEOFx0Yw6uBdpL1DkpwZJwLNIqC6Ecq//6MjngTl8OJ5sXEa6rJREZe51GlHSs+xGQJTNjplAtHMOXCEQghaKhupTC/gpKDZRg61FU0Ubi7hoOb62mfIlQNbBEG0QkWKmoUIoZGYQ6ED1GA0Z0GL/19O/V7a0mbnsQVN41uH/UfiAzcd9YLVvxlFQ21Blf/YAqpw0NElStB0iEFgQkSPNdx+WGgKB0SCvYe1UfVnnuL0+XE5KOomzYMQ0cLoF8KuP14ohPCGH9eNuPPy+60TtcNGqpaqSlvorKwmspj1dSWN6HXNTHl0qEBsjhwGIbg1ad3UnugjvPvGMeoLmoeDTT6FYbx2GOPoSgK3/3ud9uXnXfeeSietOttf9/61rf6a6dPqTvhIj7FTHxGVK/2K6lt4bkvj/L6luM0OwKQWyLQAmVgDKAMHIxg6FoDTD9rFyj9FDjewuVy+TzqxtCNgEX29ARNU4lNCWfohCRmXJbHJXfP5uIfzKAyeQOTzhkSaPP8ihCCd1/YQ3V+NYtuGz0oxAn0YwRl06ZNPPXUU0yYMOG0dbfffju/+MUv2l+Hhwd3zv+5N45nxb/38vKDK1h0+1Qyx3T/4W8vqmXp0+tx6gKnYfDkqkO8eddcYsL8NGSqqATDHbMIdR8UPyM8zqaGAAOB7nl0VyQQGIYLw3AhXE6E0NENA6fuQtTXkdzS5PH58VT69TwHgaLbA/m2ggaln1M8wTKC4nI6sUb4NjpO6DomS2hV+n3zo4/Jmjoz0Gb4nU/fK6D4y3KmXz+CMdNSu99hgNAngdLY2MjSpUt5+umn+eUvf3na+vDwcFJTQ+ckDpuWxY1DE/n4L1/w/hM7uPWx+YRHn/3O4vGP95OTGMGrd86mrK6VxX9YzQ9e28E/b/VT2uUgGL3wRYifMATOkkYUi4Y52T/CdntYIhX/6Hu0xJSyNZRGZlMamU2l00WSufPP6vTTpJyM1HVXnWmr0YihaBiqCUPREIoGqgaKSvTOHTgjI1A1U/uedDxKVDZKeOiGe3uL4shI1nz8MWL16j7t7xCCpJQsL1vVe3SX0+f+IYZhsOr5ZzBcLlSTicj4eDSTGdVkctfwMZnQTGZMZvcys9XG6HPPw2QKzKjLifoGCjd+yf/75W8C0n6g2LiqiH0fHiPv4iHMXBD476Y/6ZNAufvuu7nkkktYvHhxlwLlxRdf5IUXXiA1NZXLLruMn/zkJ0E/ihKdEMbQKWlUfVSKqnXf8ZbUtjAvN5FIq4ncZHfH8PGecl+beRJFCfzohaJCP+5WT0Wvt1P5r124ypsBCBubQPxNo1B8nAnxj8PvZ2U/ozbSPH++4p2v30nazx8nPIRzzvgDNTqaGy64gMxpfbtROFxdw7/fX+Zlq3qPy+XCZPKtQLnwW9+h5MA+mmqq0V1OLLYwXC4nztYWWl0uDJcLQ9fRPY/H9+YTl5pO5phxPrXLMAxW79jJgsmTOi3/5/P/YcYV12ALkGNvINizpZyNrx4kc04Kiy4ffGn9ey1QXnnlFbZu3cqmTZu6XH/TTTeRnZ1Neno6O3fu5IEHHmD//v28+eabXW5vt9ux208OT9fX1/fWJK9RnF9ERqZy1rTNbcwensCb24oZlxFDcW0LAH9fOsXXJp4kCBIUKap35+vrlh/FaHaRdMd49HoH1a/sp+GzIqIXZ3e/80DH5cLiY6fJgUB/o3CCwP0EAMPpxOJjgTJk3ESGjJvY4+2fvvvr7F6zkiM7twIgDJ2MvLFYw86czTU2NZ3I+N6FwP75+eeo2bebtZ99wv3/dw9hFis7Dh+mtbqKy+bO6dWxQpnC/dWs/PceEsbFc/nNYwZlUrpeCZSioiLuvfdeVqxYgc3WdRrdO+64o/35+PHjSUtLY9GiRRQUFDB8+OkK8NFHH+Xhhx/updm+QdWUHs+c/PCiURyvaeEHr+/ErCl8a/5wLh7n32ktJcBXU0VVEV50zHQcbyRsXAJWT2Gr6lf2U//JMSlQAEV3YZYCZdCgu1yYg2ykYOZV13N83y4aTrjzs9RXlFOweQPaGYSUvbmZsOhobv71H3vcxksrV9JUWcHPf/1b/vfpSh79+UPcdu/3efO5f3H9N3xTCToYqSxq4J2/7SQyO5Lr75jQqUL0YKJXAmXLli1UVFQwZcrJkQJd11mzZg1PPPEEdrv9tNj9mTPdDk2HDh3qUqA8+OCDfO9732t/XV9fT1ZWYObZwiItHDngoKG6tds6BtE2M8/eNoPaZgcWk0q4xd8R22rgfWQVxatTPObUcFr3VeOc1YRe7062FTHblxMnoYOgc7p1Sde4g3j6/sPQVN84yep6MxWVH6PrzSQlLsJqPXsWVN3lwuzjEZTeMmHRhUxYdGGPt9+1eiV7Vn/S4+3X7N7D/k8/4sGf/RJVVblh8flszRnGfx57hMi8MYwZMjgid+oqm3n5T1uxJFi5+Z7JaObB+7vvVa+6aNEi8vPzOy277bbbGDVqFA888ECXiYW2b98OQFpa1x2N1WrFag0OT/IZN83m+C8/Y80zn3PJD8/v0T6x4QEK0+unoG5xtbC/ej+pEamkRvRt5EdRVa/6wcRcmEPl0/mU/9E9hGwZGk3sksGX76ArBuf9k/9RfRBm7HTWs3nLtTQ3F6AoGocO/YYpU14kOurMvhyGyxnyI2aO5qYeRwkdKivjk2ef5u4Hf4KtQ26WKbnDGfHr32HthVgzDCc1tRsQhoO4uNloWugUFGyud/DfP2xFNWvcet/UAZ2ErSf06t1HRUUxblznH1VERAQJCQmMGzeOgoICXnrpJZYsWUJCQgI7d+7kvvvu49xzz+0yHDnYiEoIY9z8TLasKEMIEeRzfn23bWflTu759B6qW6tRUPjWxG9x16S7em+BqmK4vJf/xZQQRsr3pmI/Uodq0bBkR6MM0qHNUGNl4UpeO/AaqqKydPRS5mbMDbRJfSLaakVUVfCDfzzTeUXb17A77aKAcDo5f8FCLhybB0Bx8Yu0thYza+ZyLJZk1nw+mU2brmDRwoIzHsZwubD6aIrH3uLC0eIiMs7q02tcT6+htU3NPPen33Hdt+8hJT7+tPVRZ/FxORWXq4Gt25bS0LAbAJstk6lTXsZmS++54QHC0eri+T9twbDr3Pqj6d1Gkg4GvCrPLBYLn3zyCX/6059oamoiKyuLq6++moceesibzfiU1romLBY9yMWJJ5FsHwejf7r2p2RGZvLk4if59NinPLnjSaamTGVmWu/yCzS3tOBqbe2TDWdCtWiE5Z1+kRrsGKrWHg4abHx27DO+u+q7TE+djlN38u1Pvs2/LvwX01On+90Wd9B234kNs/Ho/ff1y4YnV31BVUND++vW1mLCw7OJiMjt8TEM3eV1J1khBBvfO8LW5YUYhiA5O4qLvzWByDgfjWALunXmd+k6f3j8N8y98lrGDxvW7yaLip6lufkI06a+hskUzfoNF7JjxzeZOfPDfh/bl+gugxf+ug1HZSs3/GAqsX5KsRDs9Ptqt2rVqvbnWVlZrO5j/oFgoOJILfu31jJkePArV8VRi+Ko7PV+ra5WCuoKeGTuI4xJGMPIuJE8tfMpHtv4GG9d8VbvbNA0VDn54BcMsxmXw4klCAXK6wdfZ0ryFP51wb8QCCY+P5Gvf/R18r+a3/3OA5BTixPHxs2kuORljh79O1ZrKqpqIy31K2c/hsvl9c/6+N4aNn94lGlLckgaEsVn/93Hp//dy+XfmeTVdtoQwqC7sIPfPfUPcsZN5KJZs7zSZlPTIaIixxITc9JPsrFpv1eO7SuEIfjf0/k0HWng8nsmkjwkOtAmBQ3Bd7ULEEII3nl8A2FhClOvDYFMhUJ3//USq2YlMzKT9w+/z6y0Waw8thKgT1M8YeHh6LrMJOsXVBWny0UwSmchBKoSPI58gR79FMLodD5Ski+loT6fw0f+hBA6CfHnkpv7wFmPYQiBycv5f0oO1RIebWHGZUNRFIWVz+2laE+1V9voRDcjKM+8/Q6q7uLrV13ltSajoydyqOC3lJW/h9nk7uiTky722vG9jRCCd1/ey4kdJ1j4jTEDtipxX5ECpQMRETq2cI3Y1IhAm9ItwhqHYen9vKqiKPx09k+597N7Of91tyPw9XnXs3jI4t4boSiedOsSX6MKAyNIpx2vHnE13131Xb71ybdw6O7oq2cueKabvXxDoAPboM334uRrRVEYMeLHDB16D4bhwGLpvhMyAIuXP+/oxDBaGhyUFtSRmBmJZvLt90kgzjjf9uHGTRzfsZmHHvqZV9vMzFxKTe0Gdu/+LgDR0ZMYNeoRr7bhTdZ/VsTxz8uYdl0uY6eHTvZ1fyEFigdFUcgcl8LutdVUbVuJqgh3hIoQIER7tIqCOyd5x7u0TtcRpUMac0Vxv1YUUM1gMoNqAc0MmvtRMVkxhUVgtoZjslpRehxK2lcPFJidPpvlVy9ne8V2MiIzyIvP69NxFDUIQp0HC7qB2RycP9dF2Yv43fzf8fr+1zGrZp5Y+ESv/ZkGEm6Bcvrv2GTqeTFSwxCYvBxWPnJ6CnvXlvDW77eiKKCZVb5y/2SvttEJIbqc4tlx5Ajr33iZ7/30F5g0736nVdXKxAlP0dx8BMNwEBExosvPIhgwdIPNy46SODmBWQsHRwh1bwnOK16AqC07QYRWTuvad2iT/m0iw4370R2G2Nmtvy0yUXR80f7UQBEGqnChCB3FcKGgowodDBeK4UQYLlrq6xCGQVh09MmO/wx3IIq9iabIBfQ18Xm8LZ6FQxb2cW83ra0tbNj6JWvu3dfnYzhrazBaW7CmBs7LfmJELPQz1b2vUXQdcxD6n7RxUc5FXJRzUaDNAAIfkh0fHs76L9eyafPmPh/DZHfy0l/+iKqpKCg4BLQYgjizhtp+4+MOi1ZUFUVR3M8VBVVVEUIwZ/55jJlyMuW/Zla54nuTKcw/QWujk6wx8d3me+oP4lRnHKCstpbXn/wLt933Q2J9WAwxPDz40xPs21qB2uBi8ZL+OwcPVIL3ihcAIlOSKT6qkHXP64E2pVvyn/sPTceLCGR1hvDIcMaPHsu8//fzAFrRf3760I8CbUL3CAO1izxDki4I8FTY0jkzWDpnRr+PI4RACIFhuOvhuFwuhGFg6IZnme5+1F0YLh2Xy4Whu3C5dDZ9sYYDe3Z3EigAmqYybFJSv23rqf0dP4oWh4O///4xLrzlGww7Q16swcSaj45izokkKavnI2uDDSlQPOhOg0NbKkjK8t0dhVdRINDzK4qi9Kp4icups29dGXUVzWTkxZE9LiHgDo3g+zvuurrt1NZuJDx8KImJi/o85BwM50rSO/Q6O/ajdWhxNixZUb36DJUOIyImk5neBAMf2bcXp957J3qvIqDt12UYBr/78x8ZO38R88b7tthgKFB2pA79eDML7hgbaFOCGilQPOz98hhOu8aCW3tf8E8YgtKCWlqbXGTkxWH1Q/Y/tzjweTNnRdDzrJvCELz/xA5KDtYRFW9l+ydFzLx8KNMGeKbYoqJnOXDwETQtAl1vIjn5EsaN/XPvxUawVLELcsSZ/TL9Tsu+ak68sBdcbv+18KkpxF0zwi9C02G3Y4kIrLO/wGh/r0+8+CLRSclcf37PMnQPdFZ+dAQjxsyIScmBNiWokQLFw4FNxwmL0klI7928qO4y+ODvO9vD9cKizFzx3ckkZPhufhUIihGUjg7B3VF8oIbi/bVc/p1JZI2JZ/lT+Wx49whjz8kgLCqwwbPCR/2FrtspOPw4GRk3kzfyZ5SVvc2evT+gPOl8UlMu69WxgqXTlfQMIQS1bx/CNjyGuOvyaNldRe2bh7CNiCXcD52S02EnqousrP5EeEZQXvvsM2pLinjoByEwleoHmmrtVO+sZvIVwwZtEcCeEpzuzX5m/Tt7KT3kYMKC3lfNPbCxjON7q7nk7gnc8svZOB0Gr/92iw+sPAWlv4XlvUQPTWhpdAKQkOkWbm01JpobHD4xqzcoPjqNLlcdut5MfPwcFEUlNtYd2VJREdxZLUOaYLneuwz0Wjth45PQIsxETHUXB2xYVeSX5p0OB+YzVJz3F4oQlFeWk//Jcn5w3/2y2KWHz1cWgqYw/dzMQJsS9Az6ERR7i4uty4vJmxnPtCW9D7etLm0mKsFGzvhEAFwO3S+6QUEJ/Ki/u3RsjzbNGBmHyarx8b92M2xSIsf31ZA6LLrXI1ahhMWSRHh4LkcO/xlhuCgvfw9FMZE38uFAmzZgCfRPog3FrGFODadxXQmmRBstnhHW2K+M8Ev7QlF8Jrx7SqPLRWVpMd96/EnCelg0cKDjcuoc+KKUrJkpfnEFCHUGvaStKmpACJWcCRl92j85O4r6qlZ2rSmm5GANZotG0hB/eWUH9gokDAE9zHYZHm1hybfH01Rr54v/HSQ6KYwLvjmwneUURWH8uL8gMNi1+zvU1m1h3Li/YLXKeWdfEiyDKHHX5mE0OKj8x04avzhO9EU5WLP9k8bcEhaOvbnRL22dibr4FKLPu4j0AE81BRM715eitugsuCAn0KaEBINewiVlRRERa/DRM/nsWn2QuddO7FXYV+6UZIrmVLP6JXe9h9iUcC660w8dbxA4yfY2i2zWqHiWPjwrBCpFe4/IyDxmzliG01mDyRSNqg76n5zPCfTPog1LRiSpP5yOs6IZLdqCFuk/X6vYuDhqq0/4rb2uUK1WtLDgz8rtL4QQrFtRSERejCwG2EMG/dXSEmZi6S8WsPG9fez5vJj//WoTMcmCGZeMYsSM9G47UkVVWHjraKYtycHe7CIhIwLVyzU0um6YHkfQ+AwhepH59iSDRZy0oSgKFou8i/QHwfbNUkwqlgBMYyanpVF4uMDv7XZG6Ue+64FH0f4aqLCz8MZRgTYlZBj0UzwAZovG3KvH8vXHF3Peze6S6Cv+s5+3fr+Wlh46cUYnhpE0JMo/4gS6rRLqD4TRfbVSicTfBFy4BwGpWUNoaGwKtBmSDqxcfgSSrAwZJW9WeooUKB3QNJWx84Zw8y8WsfDWEVQUNvPcg6s4tLkk0KadTi+TpPkCEUxJJyQSgkO4BwMx8Qk4XM6A2iA/iZPUVTbTtK+OWecPGXQjyP1h0E/xnInRc7LIHpfCB39bz0fP7KWquI6Zl48Kmi+X0dJMw6pVHJg7r+c7dbBd2O0YDQ1oiYldb9smfrp6v551usOO+bzgrmEzUIgrLendZ+1lisIiePK2u05bfmqkyKk5ZbqKJOm4zWnrPeuEZ52C8NScUbEAVgwshkFb0n/379Fdl8Z+6BAxmkLBqlVYN2xoz8R6crvOj2daf+ry3i7raptT16uqysKFCwkP940vwpbDR2l0uFixeQvnT5uKy+Wixe6gyd5Ks8tFi9NFs9NJq9NFi9OJw+XCMAyE7sLQddB1T1p9HaHrCMP9aHR4LoQAVW3/U1QVRdUwqSqqZqLw8EGMlkp27liGUNzrUTRUxb2domjt+yiqZ7knt5KG+9LjrkTknigSiPZrjxBtywAhqHS4SLSYen7H3fY5nVxw+jrFnYzy1OXurU+9Lionl3e8znqWb1hWg2FTmTgrcDXHQhEpUM5CeLSFax44h9Uv7WDLslLKCqqZf9Mk4lID7/ilhUcQed55jPz5LwNmw8Gn/4FSWhqw9gcTYU2NjNywLmDt71v6VV5feoVf22zrhAxdR7c7sLe0YNd1WnQDXTfA02EJz3N9ZDbP7jvAmBHDGJueimEY7ccxDKP9EWh/fepfV8u72qe71139dbRl165dDBs2jDFjxvjk3K3ckY9lwlTWPvsPPn87AaGqKCYzqtmMppkwaRomTUPTNMwmE6rJLRIUzSMaNM0tOjSTR0CooHVYbzGjKCpCGCiGDroBTrfIMQy3kFFNKvPrPqCpVEMxDBA6CPc5wtBRMMBwL0O4nwuPHGnTrQZ41Cp0FhFqJ4mwv7mV3HCbW7h2Egiezc842ixOeXrytdJWCPa0/Tvu0/X2HV/rLhPVWxcxZl4qJousp9UbpEDpBkVVOO/mScRnHGbdW4d46efrSRtu4dL/m92ebCwwhgWu6XbkVL/fsDQ3B9oEv9N2N62aTJhMJqwR3Yw2DM3GVniMmOQUsrKy/GJjXykqKvJp4rK80aP5ctVn/P6Jp33WRneUHN3MwU2zmX/RD33eVuDGFrtn50f70UURs5bIuju9Rfqg9JAJC4bxzccXM++6YZQfaeG9JwJ3Nwv0WBw0O5tpdPgoH4IUKH7j6IRJAW1fBMnU5kBBCOFTgXLV2DwUU2DvP+trihFRg7tqsTAE+Z8UMHykQmRciBSiDSKkQOkFmlll4sKhpI8Ip7q4FUPvXR4Qf6IbOo+se4TZL89mzstzeGDNA9h1uw9akh2XJIgIkQgewzDQNB8P9wf4VDQ4HYQP8gyyRbsrqW2wMf7SyYE2JSSRUzx9wGwz42h18M97V5I+MoakrAhmXDoazRw8eu+1A6/x+sHXuW/KfdhMNh7b+Bg50Tl8e9K3vdjKQIniCf5ObUCcZj8RKoM9vhQoDpeOEuBCdIbuwjTIExPufH8bifE6aSPiAm1KSDK4vz195MI7plO8r4bdXxzm8LYGivY0Ury/mq98fy6ayY8i5Sx3i3u2LeP27ZFcsOzfgKDG5YD3/kqJ9pJn304PJx3RujrkqZEano2NqlaKYqI4+v1rPD5sJ33bFQUU3SBhXy2KKfx0ezs6pImunc4QJx3N2l6fmvhJa7EjVAXDYunsSNceDdLRI7+DjYrieRcK4wNdtKQHCAhoBl4lwO2HEsdr68kvLnH7z7R/39oiUtznsqG1lY37D3Coth6zxYLFbEHTVFRVRVPbHhU0VUNTVfc6RcWkqWiqhklVMGua+09VMKsqaofPpsnpcDu6BhDd0LGog9cptLa8mcJCMwtvHCF/N31ECpQ+oGkqQ8YmMGRsAq2NTkoOnWDZP3az8tltpA5PICohnKzRCZjMgflxOo/s5vz/bOW1mRaUXz+N1RLJc+9dRYw1mjsue/3kLWbHPCYdfz+eHCtd/qja8q94MtkOVdtEiXBrC8PwhAOCq+woJx5+kMS/PH2yjbZQy7ZjK22XbNqXKerJcEw6but5rXTYvvwnP8WUnkbCt7/VOTS6Q+QEhuFe1yZwhHDbabjXl917f29Psd8RquZ+HwHudIIetwoNqAmvrF1HTU0NMbGxQNtXT9A2ISwAIyObA6oFUVaJcDoRLhdCeL6ThtH+XAj3d1e0fYfblrVFDLVtKzrfRyi6iyO2SMZ/sQuARl3njqwkHhzmvzBXQxh9yjQ9UMj/cAc2i4MRs7MDbUrIIgVKP7FFmhk2KZXI2F0c3FzHwc117hWKgaIIwqNh2MQUJizM5fi+SgQKmklDd+moqkpUQhgpOdFYw829bvtMjot1Tz5Czs03sjtsJUs+/wYoEBEbyz8u/i9aTEp/3u5pnK271FpaMFk0wlNTvdpmR1STCc1sxhLR93TiIgQuooaqgq4HTqAI0T7IFtyIgE/xCGDu5EksGRs8Kc3v3n2Uw82+8EE7M4buQjX1/Pt6pKqJJruL0WnRaAGenuovjlYX+7bUM25Oogwt7gdSoHiJK+6bTdHeKoZNTqW1yUnBlmJcTp2KoyfYtaac/NVVZ9lbkDs1mkVfm9LjUZezXYSbdx8i69EXedN1Nx8Xfoxu6CzOXkxi2BmSsoUyQoSO00E/MFTVU1ogMMgMraGNARh+nsk0DB1N7b5Aoks3uPfV7Xyw051TaVRqFM9/fQbJ0aEb9bL/88M4XRrjLhrYFdt9jRQoXiI2JYLYFHcCt4gYKwnpee3rWhocHNlRQc6EZGwRJtwJGBUMXdBQ3creL4+y9aNijn/5OOHOjaccuc0xROm0qLWlhdGTp59mh9FYB7p7aDXGGsO1I6/1/pvtMX66IoZI5EZ/UETgy64ZQnTyc+gvdnsldnspEREj0TRvdkaBF1PB9pVMsJhw9UChGIadpqbD2GypmM39c+wUQkftwYjf61uOsyy/lMevnUharI1b/7WRe1/Zzst3zOpX+4FCCEH+ikMMG2EhKj50RVYwIAWKHwiLsjBmXuZpyzVVITYlnNlfGYOrtoXdGyZx0WN3E5fSdaba9myUbfPRXUxNtK55C1vukEExqgB08H4d2CgEdqRIqIrbB8ZL02FHC5/i8OHHEULHbE5g4oR/EBMzpf8HFuK0dPv+Jhh/ebrofuqrvn4nO3d+C7ujHEUxk5v7AEOybutzm4auo/YgimfH8TryUqO5eqr7GukyBOsOn+hzu4Hm+O4qauptnPeNSYE2JeSRAiVImLV0Ejs3rKJwczFxl4zscpv2Oh9nuSsx5YzFVfucT2wMSrzQaTubmnjrnvtOPfDJpzYrVzz6CGoAE18pQvgkWVqTs4kntj3BlvItZEdn850p3yEr6vQsrHpEJC/c9FVURSHW8/0TyslaOsJi5tJ/PdWj0NnGxv0UFPyWIUNuJyV5CXv3/ogtW29kwXl7UJT+zdcHozgIBgwBprN8f4QQ7N5zP1ZbKuPG/YXyig85ePCXxMZOJzqqr9MURo+S0Y1IjuT1LUV8eaiK1Bj3iENGbFgf2ww8m97YjtkMaSNlaHF/kQIlSDBbNMLNTo5uKWbixSP6nMOg5u+/Jm7p17xrXBCjKLjrePSDRc/9G3vHVPJCnByiF4J1D/wY4XBAQAXKKYXLvMSDnz/IxrKNXJhzIRtKN/CNj77BO1e+Q5ipcwfxlX/89azHeftrt+NyOnskUOob8gEYNvQ+NM1KeEQujU37aWkpIjw8p8/vpY1g8JcJ/IRcZwRn1/IuVwPNzYcZO+aPxMZOIypqHMePP8eBAw8zbeprfWpTMQxEDwTnTTOHsHxXGTc9swGA1GgbL3xzZp/aDAZKS93vWYYW9x8pUIKI+beMY9m/9vHh779g8T2zsfay1o9wObAXHMN24S0+srCX+OUarbSHC/eV2JhoiIk+43pXeBhC1/vVRn8RQng9sqHOXsdnRZ/x8JyHuWrEVeyv3s81713D37b9je9P/37v7FNVdFfPzlFEeC4AxSUvkZJ8Ka2txwGw2byUFl1O8ZyGIQSacubRDJMpEoslifKKD0hIOI/y8ncBGJL1jT63qQod0YNk5Tazxst3zGLjkWqaHS5mD08g3BKaXVNLgwOAmRcOwICEABCa34IByrAZmZzvNPjsv3t54fufMG3JUCYsGdljJe7ctQ5LetLgyj2gqj73SBSqBi6XT9voDkUYXk+8pSru1GFtJRCchhMAm6n3jn3CpGH0UMTFxEwiM/MWDh78JQcP/hJVtTJxwjOoav/TogsvfRf0RgeNa0vQ6x3YRsURNi4xpO+IDc4unBRFJS/vYXbt+i5rPnenZU9Pv4GkpAv73KYidPdvpwdoqsLs4Ql9bitY2L1iL5rqYtz5owNtyoBACpQgY+TcIaTmJbHuuc188V4xxbvLmff16UQndj8nW/efPxF5yXV+sDKIaEsc50N0k8ntIBpgvN1BRlmiWDJsCb/f9Hs2lG5gW8U2cqJzuGPCHb0/mKpi9ELE5Y38Oelp19LSUkRMzBSs1uTet3lG+neeDLuLiid3YDS5MCXYaN5STsySoUSde7qj+5na95ZQ8haC7guvJSddyJzZK6mt3UxY2BCioyf26zunCIERwqKut+i6wa41JeRNiMAW2fu8VpLTkQIlCIlODOPC+89h6NpjrHphL/99aB02k5PEVBspY9JIHhZH0pAoIuOs7RcQ5+71tB4uIfFPffe6D0kUpd8+KN1hqBqih9MXvkLxUYf3izm/YGj0UDaXb+b87PP51sRvYdG6z11xGqqGq5fTYFFRY4mK8n4J+v72iS27TqBXt5L6/WmYEsIof2IbdR8eIXJeRo98w4QfRHNvEYIehYjbbOmkpl7ulTYV0bMonoHC4U3FNLVaGX+JLAzoLQbPtycEGTl3CDlT0jmWX0Hp1qNUHK4m/+NmHLiHwi2qk5FTEhi1eCTGHx8h6Yf/L6SHofuEovg8A1WrqvLx43/CGR5xSop+N23RNSmbNlA9Zhyu8HAwDBQhUDwh4YowUDxpykXHVPuG4RZYhjs1vyIMdxi5IaB9H0HSkcM+eW8WzcKdE+/kTu7s13GEpqEH2E/HTf9diYVdB1VBjfIItfbSED3b3150lCZbcN1BByQLsDD6HZUVSuxctouMdIXErKhAmzJgkAIlyLGEmcidkU7uDHcNDSEETbUOKg5XU7TlGPu3VLFrcz0211fJWS+Iq8ln/EVjMHshvbLdpfPb5fv5ML+UmDAz3zt/JBeM7UXaer9dEX0rUJY8+AOqS0pP3hULcbLN9tw0AiaMJToxCawWUFRQFc+jilBAVTVUVUFRtfaicIqqoKoKqqq1F4RTPY+aqqBq7mJxJRdd5NP32F8UTcXlDKyfDrQlFu7fF882Kh4+PELVf3ZjzYnGVdFM+ORkFK1nxzVlDCE2xXflHfqCIXrirupdFEP3Wt6cYKfiaB1l5VYuvj14yhsMBKRACTEURSEyzkrk1DSGTU3jHN2g5EANe5fv4ERVCweWlXFw/XHm3jKdjFEJ/bpYP/7xAf67rpCvzsnmYEUj33phC+/dM4+x6TE9tdb3kTxCuEWAD0lLTSYt1Zs+Er0n2EfGhKoFPNIJ2nwt+neuTPE2Er82lrplR2jaXEbY+ERiLxvWcxsMA1OQdcwG/v8OCWGgKIOji9n5/laiwlvJmeylSDQJIAVKyKNqKpmjE8gcvRCAqmP1fPLkWt75807CrXbGzk1h+LyRxKdG9Dq3ygc7S7lldjb/75IxuHSD3P+3jKuf/JJ9j1zco/2Fy0VLUV2v31OvcE+u+7YNSfd4agUFGtGDjKk9wZYbi+2evvkSGIbRo3ww/qQnTrLeRhH6oIgobK53cHC3i1lLhqDKa5FXkQJlgJE4JJrrf30RxftOcHjtPratqmLTp7XERLVywV1zSB4a2+NjRVg1SutaEEJQ1+IOQR3X49ETD77us/wwgiLpHkPTMFzOQJsBiIDrVUPomLTg+k4KEYDzYgwOgbL7492oimD0wrzuN5b0CilQBiCKopA5OpHM0fOY1eqivKCW9a9u5u3fb+Dib08ma1zPpivuOHc4339tBxf/+XOqGu0kRlp48uapPbZDtVgIG3LmBGheQYh++boYwuCfO//JWwffwqJZuG3cbVw14irv2TdYUJSgCFxxO4MGtlMUuoGph/k/eouu21FVS6+na7rLg+ILFGGgDPAoHt1lsOuLMvImRmKLCC7H6IHAwP72SLDYTGSNTSTlx4tZ9odVvPvELoaPhPPvPQ+tm7u8a6ZmkhBp4cOdpcSGm/na3KEkRfU/mZZXEQKlHyMoL+19ib9v/zvX5V1HvaOen335M5LCkjgn8xwvGjnwCRofmcDWVHSbYBjd/rZ6S2trCbt3f4/auk1YLMnkjfw5yck9T6Lmronu5xMzCKJ4CjYV0dxqZfylMrTYF0iBMkiw2Exc9sBC9q8t5LOXCti9Yj8TLuo+2+GCvGQW5PXNQbSnyaoMYbD8yHJ2Vu0kNzaXK3KvwKz27G5E9NMH5aOjH3F+9vk8NOshhBAsO7KMu1beRf5X8/t8zMGKEQRDKAGZyjgFwzAwe9kHZfee79NqL2HUqF9zouozdu2+l9lRKwgLO72wY1c06rrX6wPl/+NSnChnzJWY1lhM9qFXoS95dZoqICKwjumnc3qw9s6i75ORkkpCRmRgTBrgSIEyiFA1ldHnDiV/xQH2f36kRwKlX/Rw+uWxjY/x8r6XyYnO4eV9L7Pm+Br+vODPPbsrF/3L8BBhjqCiuQLd0NtTvkdZZB6D3qLgvTTz/SewCsUwDCxeFCi63kpt7QZGj3qU9PTrSE25nFWrx7F7931Mm/Z6j45hVlTCvewP4lRUptz5rlePGUqUH6mj/DdbuPgKGVrsKwa+B5OkE5XHGqisNBOX44c8Da110FR51k2qW6t5Zd8rfH/a93nvK+/x89k/57Oiz1hRuKJnbQjR58rPALeOvZWdVTu58p0rufztywkzhfHCkhf6fDyfEeh5i54QBDYKQAuwHd4eQVFVCyZTDHV129wO63XbAEhKOr/Hx4jUVOq9nQ05aARpYMh/fytREa3kTJKhxb5CjqAMMqLibcTHOti/pRaL+gXnfmOebxu0hJ91dYOjAYFgeOxwADKj3PVO9lXv44KcC7o9vBD9czqYkz6H5y56jncK3sGiWrg+73qGxfQ854XEjdvHIQgQfve0ON0EL4+gKIrK8GH3s//AT6msWonTWUNs7EyGDPlmj4/hFAKLl0dQgkCPBozmegcH97iYdUm2DC32IVKgDDJskWau//WFrPnvDvLXVTPtWgfh0X2YI+4BQjGhhMeedZusqCyGxQzjNxt/w5G8I3xw+APibfF8c3wPL779nOIBmJQ8iUnJk/p1DInPKw70CEHPas74EsMwsJi864OSmbmUyMg8qqvXYgvLIDXlsl45oLYaBmE9zITbUwbzAMruj3ejqoLRC0YG2pQBjRQogxBVVZh+5Wj2bVjD1jc3M+9rc3zSjnP/jm5vs1RF5S8L/8LPvvwZf9zyR3Jjc/n7or8Tbj77yEsbiqrStH4dCbd/E9Vm84bZQYmzsZFtv/o1isUMKO4aPp46P6fTYVlX6zuuRoBwZ/1EuLcXhoFir2VIWBOqpoGqoWhqe9p+RTN5HlXPOo2k/C0sPziOOHs5YapCuKYSrmlYNBOapqGqJorVSFy2WDTcIkJT3NMxGp5Hxb3c5Fnmft62bdsy97YqCgqgKe6vmKa488fahUKTy0mDw4mqKO4/9eT2quKWs96OOhKe8yaEAU4HijCwO+3u5W3r8XxeQnheex495160fSKe9U26i3BV9VRMMIFlJNGJI9ENwYlGO6riQNVUTIqGpimYNA2ToqJ2MVJiNwThQZY8LlQ5GVocJUOLfYwUKIMUS5gJISA8IdYnx3dsWU7h935N+neu7nbb7Ohsnr3o2T61E3fTjRR983Za8ncRMX1an44RClTOno1J10lKzfI4WrjFQs9qnXTRGbctUhQURXF334pb8KGqbFv1Hhkjh2CLSQJDB11HdHw0DPdzz+vsCyYjEgQt9kqadcEJA4oMgd3T2RqGwd/JYXScCwN3h+1+BIMOz9s6dGjfTtB5uUdHtessgWhfZkrNJn/rPhRVPW1b0V7zT/E89m7s7avHnmZR/UFA63Sc9lOquJd9zaVT8sq7lHpEkLuYpEdJobjtVhT3/u3LlM5iXlE50uJgSJjVLayEjma4mFq0nK9MerWD8HGfJ/efgnFaRI37XTahsO29jRxubeo0HRdzcBd1I8a1n4iRTXuZmV5OY1SSe+8u9G1b1I7JHGQpB/xEe2jxJZMCbcqARwqUQYpmUomJdnJoQyETl4zySt4GV9FBqn7+HWrWHkXRDLJ/cz/hV9zhBWvPTPjkyZiHZIEe+EJ1vsSZk03qjBnkLVjg87bKd37K7m2ZTB8zkZTZV/RonxhgSDfbbF32Gs9Nmd1v+wLFhmefIvLO94iJTvRLezO6WFb6yGTeurKPhSOv6j5vSvH/fgomKyOu+n99a2MQsHPZbjIyVBla7AdkFM8gRVUVFt05m8oqK3vWHO/38Yz6agqvvRxHaTkpNy8gb9Nmn4uTNhRFRQRBJV2foutg9v1wst7ayJNvrmZhNuT0UJwMFhQUn1du6BYf+324B1Jkt3Amyo/UUV5hY8IlEwNtyqBAjqAMYlKGxZGc7GTNq4c4cegY066ZTmRc34Ztm99/DhQTQz7c6mUre4AWHJV0fYnQdRST73+u9WVHAYUvC1s5R9dRpN9CJwKejK4Hc1L2ZieKqmCxycu7t9n53haiIuzkTPJDmgaJlMqDnat+ej7zLk/l0I5G/vvjNWx9Z3ufjmMZPwvD4QyIUFBUFYKiUJ3vELqO6ocRlLCEDEaHVWFSBNVHdvq8vVDC7bsRvKErLofOR0/v4pnvfc4z3/uc1S/vxwiG0KoBQlOdnUN7dcYvkFWL/YWU2IMczaQycckYRi8YyYbXtrNuWTXNtRsYe+E44lIjenyciod/QFhWNM5Du7HkTfChxV2gqhiu/k3xGM3N6I2NCMMAl+ukA6jnD5fLs04Ho8M6z2u386jHcdSzzNB10E86k7bth26AMEDTUExmFE3DfuQI4dOmocXGoMXFYYqPR4uORvGIEqHr4KPRjOqju/j4f0+TnJTEyMlzKGyN5qpF00nIlfVFOqIoSlB3+FuWF3J0ZxXzb8rD0epi3ZsFJGREMu7cjECbNiB49oG1gCZDi/2IFCgSwB3VM++WqVhtW9n5eSU71m0gJdnOrBumkTkmqdv90/75BrW//S5Hrr0OUMj9bBVaQorvDQd3REsfsmQ2bdhI08YNtGzbTuvu3agREe1RLSgKqIq7EKHnuTvM1rNM9Wynau5ba1Vz76t6ttfUk9upmjsst+0Ymmcb3fAIFh1HYSEtO3YgWloQDjuG3YFwOtvDKFKcTpjrm6R6jeVHiI5LJHfMRD744APGxgpy533FJ22FMgIFI4hHUI7vq2HopKR2QbLuzQJWv7RfChQvUFvR3P5chhb7DylQJO0oisKM66Yy5Ss6R7eVsuODXbzzl3xio1qITzYxbFYuI+cN6zKHhBafQsJjLxP/iJ3ax++n/Ds3kP7iZ/6xW9UQvZji0VtaOHbzzdgPHsI2fhxhkyaR9czTXeaPCBa2/OSnqE7vT2MJXedo/jqGDxvLkJmXccvwKVgior3ejq8RQnDixCpqatcTHpZDWtpVqKp3w2Dd4bXeFyg1TQ5e3nSM6kYHF45LZXpOfJ+OE5Vgo+JoPa1NTpx2t2BPzgn8Z1lW18pfPz3I0RNNzB6WwB3nDsdiCt7fWlfs/3QvALf/8dwAWzK4kAJFchoms0bujEyGT8+gYGMRpbuOUXmsnk9eLMQwYPT84WfcVzFbiXvgrzReOZPW9R9jm9V9uvp+o6ruaZUeUnjDjdgPHSJv5w53IrJBysb//YEN+0o4YURy38XTAQhPDM277aNH/8bhI3/EZsvEbi+lvOIDJk963j2K5TW8H8VT1+Lkir+tparRTly4hWe+OMJfbpzM5RPTe32saRfn8ObjW/jPD79ACIiMt7Lk2+P7YJX3RFirU+f6f66j2aEzZUgsf1l5iMITzfzu2tCKgjmwuZwxEyOwhMku05/Isy05I4qikDtzCLkz3Rku3nv0I9a/fRBLZATZ45MwWc7QuSsKttFjaPzgdb8IFEVV3T4dPSRi3lwUm21QixN0F5v3HeObd/8Al6OVqLQzi85gR9ftHC38O9lD7iA39wFOnFjN9h1f53jxC2Rl3urVtlQvT/G8s72YsrpWVt4/n4zYMGY9upLvvLytTwIlPj2Cm342i8PbKlA1leFTkrCG9246Qigq3hQoXxysovBEMyvuO5cRKVHc/78dvLblON89fyQZsWFea8eX1J9oob7RRvaMvECbMugIrXE2SUCZdOl4VEWw/Ok9vPzjjzhxvP6M2yb89AkqX/scx47PfWKL4/hxql94gZZdu9yX0144LwrdwDoyBB3dvBg48Oaff0BmUgwma1hIixMAw2jGMOxERo4GIDJyFAC1NRu92k7/qz6dTnWTgwirRnpsGKqq4OqnE254tIVx8zMZMy+91+IE8MxjeW+cqO39tE3ptAW/BLOz8amU7K0AID0vIcCWDD7kCIqkx2SNT+erf0inuqSR5X9ew4q/reWqn57f5bCnqKsCwDxmZr/bNTxRNarV7VNgOBwUXHQxiqqimM0YTU3YRo/GUVTkjnRRVXf+jrZHxVM3RtPcoy0I0HWM5mYMT9SOGhmJ6oc8I8GA0HWanQo3f+/hQJviFczmOKKjJ1Nw+HGcrloqKz9G08LJy/u5V9sReL+Gz6JRKfx55UG+88o2xqZH43AZ3DA9y6tt9ApF9WoVwHNGJJIabeOWf21k1rB4Psgv5ZLxaWTF96zWVjBQvOMwCXEt2CKlc6y/GRxXZIlXiU+P5IK75/HWb7/kpQdXMO7cNMZdOLbdu104HRTffj1p91yHYu5bpeT6Tz+l+p9PYxkxgsYVKzDsdpJ/+AMizzuPY1/9GuFTppD9/HMAVL/0Eif+9W8aPvrI7cTY9gcdnrcVbxEYDrezad2bb2JKSUGvqyNi1iyy/vFkP89MaKBoGg12HZejFZNlYBRYHDf2z+zd+0MOHHiE8PBsJoz/BxaL91PSK152kh2fGcMfr5vE7z7az8q95Vw8Lo2HLh1z5h18PfCgqGB4zxk7wmrilTtm8buP97OntJ6lM4dw3/mhNXpZcriF7DExgTZjUNIvgfLYY4/x4IMPcu+99/KnP/2p0zohBEuWLGH58uW89dZbXHnllf1pShJkJA6J5qofzWXrG5vY/EkFW1ZWsOiWkeTOyqH2Tw9iHZJC7N19u0O3Hy2k9IEfkfzAD2ndvYeMP/8JU0oqx++6i6on/oZqs7WLE4D4m24i/qab+vxeal5+hYaVK/u8v1/w8tzC8LRYThzcQsrYud49cIAIC8tgypQXEUJ4fZSjDeGpiOxtrpycwZWTg8Q5WemdP1dPyEmM4G83TfHqMf1FY00r9U02MiaG9jRoqNJngbJp0yaeeuopJkzoOinXn/70J59dKCTBQUJmFOffu5C59Q4+/896Vjx3kJqSesRHhxj1i/v6dExHYSGHL7qImKuvIu6aa+Cak+uGf/iBlyw/BVX1Sfio1/GijSMnzmb1sjf4yvBJmG09T8gX7PjymmMIMA3wS5qiqu5pTwkAJfvdU9VpI6X/SSDok0BpbGxk6dKlPP300/zyl788bf327dt5/PHH2bx5M2lpaf02UhLchEdbWPx/8/ji2fVs+aQMPfdeNj0vMP/3I6wmg/Bwhdx5OYxZNByzzXTWNNE1b7yBbexYUh95xH9vQFPd2WAHETkzLqK2vJDNbz/F7Bu+F2hzQgIdsAz0my4fjKCEMiU7DhMb1Up4dN+mqiX9o08C5e677+aSSy5h8eLFpwmU5uZmbrrpJv72t7+Rmtp9QSW73Y7dbm9/XV9/5sgQSfCiaSrzvzGHc75mUFveQmVhHfXHT9BS00RNaSNfflDMlx+UoKKTHC/ImZHJpEtGoZk7B5Ipmgn74cNen+s/G6rV2qdMtH7Hy+ekuryYxqYmnI3VmCP7lhxsMGEgMA/0uEcpUNoRQrA/387IsaHj0DvQ6LVAeeWVV9i6dSubNm3qcv19993HnDlzuOKKnpVqf/TRR3n44YERTSABVVOJT48gPj0COJnLobHGzrGdZbRUN1G0rZgNy4qpOFLHxffN7rR/8r3foeHjj6n8y19Ivq9v00S9RbFY3WnlBxmzb3qAXZ+8wkt/+xUzpk5m9OKbA21SUKMLhQEfx6FoXhfCoUrpwVpcLo106X8SMP5/e+cd31Z1/uHn3CtZkm1Z3ivOHo6zJ0kIO4uVpmGvtuxR2tLSxfgVKLsUaKF00DasUlahQMoOIwRCSEKmszdxEjse8R4a957fH5I8EidekiU75/l8FF2de+45r44V3a/Oec/7dkigFBQUcMstt7Bo0SLs9iO9/xcuXMinn37KmjVr2t3m7bffzq23Nk0xV1VV0bdvBLfZKcJCfJKNEaf2B2Di/BHkf7CVJW/t54Nzf8Wg8q9a1JVuNw2bNnebbcJuQxpdSzboM318svcTCqoLmJI5hdFpnYng2b04YuOY/J1rmHiWh389dhvDZ1zepg+H22fwp0928Pm2ErIT7dw6K5fcTGe7+sv3uZjxfnji4hyNjXYnIxuqW5R1Jp6JAH5cW0tDQwOOyEePDxsdDXrYmzmwfjcxFi9Dp+ZE2pTjlg4JlFWrVlFcXMyECU0e2YZhsGTJEp566iluuukmdu7cSWJiYovrzj//fE4++WQWL158RJs2mw2bLbQ5MxTRz6g5w6g51MDqJWciT53LGTdP7VxgqRCg2e0dCpV/OKY0+dlnP2PxvsXEW+N5YvUT/Gbqb7go96KQ2RhO50/NGoPLrlFzcA/OzIHHrHvPwk28sXofc8dks7agnEv+voxPfn4ayXFtr9H/YuO7XHbbE6Eyu138/ve/55e//GVI2trz1OMYHcj51CMRAqkECgAHthSR2Uc/ps+cIrx0aEV1xowZ5Ofns3bt2sbHpEmTuPzyy1m7di133nkn69evb3Ee4A9/+APPPvtsOOxX9FCEEEy9dAxnXDKQgp11vHrHJ5QX1UbGFpsd6ev8DMqqg6tYvG8xfzz9jyy9dCnTsqZx39f3UeOpCaGV4WXYmEms/+S1Y9YxTMkbq/dxy4yhPHbRWF67YRrldV5+9fq69nWi9/AFEiEivtsr3D66QmgIJVAwDZOiQp3sEVGy/fs4pUMzKE6nk1GjRrUoi4uLIyUlpbG8NcfYfv36MXDgsX+ZKY4/hBDknTaQzLx03nnoS16/70t+8NgMYuzdGz9Qs9ugC0s8RbVFAEzJnIImNBLtiQAU1xcTHxMfChP9hPHemJCYQtHurcesIwBdCDw+/w3MY/if7db25jTq2b4NEkGk30OB3cn3/vvBYaVBm46lXvx16iwx/C5vACcNPYpfhdAjLsKigdJ9NXgNK9kj1fJOJFGRZBURJykjjrm3n8y/717GV/9ay6nXTER057SqxYI0Ov+rcWLGRCyahbu+uosZ/WawqWwTI1JGMMg1KGQmFheX4Dt0iHC46+W/90/KDh6gpKL6mPU0TXDZlH489dkONh6oYtOBStKdNh6YH/3+NqFAENo8NZ3B4nSx6LwzO339g4s+Y1d5BScdrYIQIHvAjrYwU5i/B10zSO/fix2OegBdFiit+ZU0R6lxRXtIzIhl2pxMln1QRGzSJk64YGS39S30ru1cyI7P5uGTH+aBrx9g0beLyEvO43cn/y6EFkJ6ehqu5NBvBa4p2s2qdRuZeda5nDh0Upv1bz9rOFkuO4u3lnDS0FR+fMZQXI72Lt307LV8KQSypwcxk/KY60RCU7t4AA5s3EdGpn5EGARF96JmUBRRw4T5I6kuqWXlxwcp3FzM2b8+BWtMy+WD93e/z783/xuJ5JLcS5g7eG6X+/XvXOjal/KcAXOY2W8mNd4aXLaek7cjPnMgrjgbNaUHyBnXtt0WXePakwdx7cmdmR3q2Te+g6ad2rdvwRsT67/PNzvX/J0FF4KkEP5XQiARSBG42QXKpdD8y0YBweA/L5qdF4DWeF4IjZS6g116D6VSY+neQlYXL2r1My/LTbKsKVg+e63Zm2pW77Ay2fgQzY79DzNY5q5F1h9Cuvr6y2XwvP8hZbPjYLn0t2kCpunDNA2ksPjrCIGJ/xEqZKAtEcjZNWF/IieclBay9hWdQwkURVRxynWT6bPiAIue3cSqNzYw9dKxjec+L/icXy35FafknIImNO748g7sFjuz+s/qWqddnEFpbEbTwydOOuEdKU1J3ZpiPHursGbGETc5E2E58hfh3Bvu5t9/uJPhM78XCkujgo8++oji4mLq6+vbrOsprKV2eSEYkthJGdiOMq3/XtK5XDzzDMZntOPGFUhSKaWJRCKlRJrB48Cz6T82McGksR7S9NeREhOJaUokJtI0scY4OjoULajOzCGzoZ65Tv+s1xG7w8w+OLVqrDZ74CMXPN/s+bBrRKAdTQSOAzmLguXCcKN56xCxKQgEmhAITUMTAk00PQshEKJ5uYamCX+5LSFQHjzX1H6oKS+q5aWFy8kZqcJdRBolUBRRhRCCIVP6sH3xdtYvKWLglP5kDEoE4O2dbzMmdQxPnfEUAGNeGMOti28l/wf5Xeu0h0xpyw7OQFS8vYPaFUVYM2KpXXmQhi2HSLly5BFf6habA7tFo3jrStJzJ4fS5IjxzTffMGvWLCZOnHjMep4DNRT/ZR2604rQNWpXFZF6zWjsgxOPqCuEaP/fQPhv5AItqha2YqwW+jlTmDEou+3KxynbthxCCsgc3HNmQnsraoFNEZWcdvOJuFwabz2ygoINxQBYNAsNRgNm4BdoqJCmGf79m92MUeOhdkURrnMGkfHTiSRdMJSGreXUry9ttf5Zl93IZ/97mWWv/gHTiA4nSU9BNbWrD+IrbXsW5HCsViuTJ08mLy/vmPVqvy5ET4gh89ZJZNw6EUwo/cfRBW9P34GrITB6hh6PGFs2l6FnOrp9N6HiSJRAUUQljvgYzvvtGaRlWHjvz2vxeQ0uGnYROyp2cOm7l3L5u5cjEPx91t+73pkk6gVKR53NzQYDJFjS/EsCussfDNF7sPVYMwnZQ7joZ79H0wRvPvnriM8qVbyzi+I/r6X8tW0UPf4Ntas67nvRnqy8pttAi7UgrFr37hyLELpACZQ2qNxdRZ8hiZE2Q4ESKIooxmrTOfnayfikhaJdlUzKnMQ/Zv2DHGcOWfFZ/G3W35iWPa3thtqip/8sbgVLsh1LRiwVb++kanEBle/sQnNacZ529HV1oetMufCnOBwOvl32Zjda2xJvUS01X+7HddZAsn87DfvQJMr/sw2zrmNRXD0eT5t1Ysek4t1XQ9krWyj/73YAEucPab1yR5Z4ohRdCIwesqQZCaoPNaBX+RiRlxJpUxQogaKIclL7xOOweNiwcAMAJ2SdwOOnPc7jpz3OidknhqSPHrHE00H7hCZI/cFILCl2qj8tQFg1Uq8ahRbTdlC1U+Zfy7KvlrLty7c7a23rNrWzXnBJJ3ZCOprNgiXDn03WU9j+SMNut5vnnnuOhx566Jj1HCNTSZw/BO/+Ghp2VuA6awBxJxw9C7vZTTd3t7sEn+/YcWk6gxD+nTGK1tmzrRyAbDWDEhWoRTZFVCM0wehTc/jmk0IO7q4gY2Bi6Ds5fM9otNLBm6Ml2U7aNR0Pohaf0Z/5N9zBf/76IKUF2znhvB9isXVfynlrTjxogsoP9xA3MQP37irQBbYB7Q+adfPNN7Nz504+/fTTNuvGT8kifkpWm/W64yPi9VaQv+FHlJcvQwidvn2vYsjg20K2WyWwoTkkbfVGNm4uRabEEJvQdm4pRfhRMyiKqGfs3OEkJ8LCR5ZTV9X2tH2H6QkzKN2MzZnCZT9/hPh4J688eTfehu7Lk2RJtJM0fwh1a0soeXo9RnkDadeNRujt/7pKSkpi0qRJod2GKkTYb+07dvyO6urNjBzxBwYOvIW9e//JweJ3QtZ+5IP1RzclO6tIV7t3ogY1g6KIemLsFibOH8mHz27BXecN/a8bKQORG6KbcGY0bg1N1xkz9wbiXP/hvafvYd4tv+9Sex25McZNzsQxOhWjwo0l1dFq/JbDefTRRzFNs8U41daGVlhJM7y39/KKFWRlfpfMzO8AsGvX42zc+FMyM7oekBACAiUMb8HrrWD79gcoL/8aR+wAhg65A6fz2Duooo2GGi9aqZsR5yj/k2hBCRRFj2DzR5tJivOSlBkX+sbV7MkxGXzKhaxd/Q3V+7fh7DOsU21IKTssATW7BS2z/V9RdXV13HXXXY2vDcNA19ubyLB9hHv2weHoS3nFCny+ahoaDgCQkX5uyNoP1wzKxo0/o6o6n+ysCyk7tIQ1a7/PtKmfYLX2nFw2+3b4/U/6DU2KsCWKIEqgKHoEFaUesgf3nC+7uqIiyjbmkzxiJHFZbQfFklIiPR581dW4KytwV1biqa7CXV2Fu7qGQ3t2Ejeq+/ITHU5O3/4UblzaeYFiGGHVgVJKrNaWOYFCLU5ENyzxDB50K6vXfI8lX0xESoP4uFyGD78/ZO37BUpo34XXW0XZoSXkDf8d2dkX0Kf+Mr5adhrbdzzAiLzQ5qQKJxs3l2E6LThT7JE2RRFACRRF1FO4s5wqdwy+b97l5Sv+2EZtSUfdGaXPhxljsOKKC9vRRvvab/C6SXC6KK+uJM5qa8sCf6uahq5bsFitWGNsxMTYsNptWO2xFFgkCbb2JuULPXlTZ/LeK/9g2OzOXS99boQIn8ublBK32x229iH4lw+vRElIGMO0qR9RUvoJFj2etLTZ6HrobpheKQn1KpWmWRHCgsfjDwLo8ZQBYLfnhLajMFO8v4bY7LhuX0pVHB0lUBRRz9LX12OPM/n+U/ejt8MXoTdS/Oc/gj1yv+wS+gwjJVZj1+rFDJpwWoev9wuU8H7xx8WFYfnvMLrj02ezZZDT57KwtF3i8dEQYoWi6w769LmMnbsepaxsMdU1m4mPz2NA/xtD2k+4aShtoN/Y1EiboWjG8fltr+hR1JZ7SOljP27FCeD3k4lwgK2T5l/L0o/faVeE1sORPo8/a3QPpuNzc9FHP0cM/R2h30I7bOj/kZt7LzG2dPr2/QETxv8bTYvcjF9HMbwmotJLvz7OSJuiaEbP/sZQ9HqklNRWCjIGKs/6SOPIHMqQPql8/vyDuGsqOnStNMK7xAPh3+UkgZ4eDT9cTrJC6OT0uYzRo55k8KBbsVp71lbdypJ6hISMrPDPwinajxIoiqjGNCRSasQldl+gsGhECNHhfDzhYOqlvyIlLY0FTzzYoeuk1w09fQYlDLuCuhuBiPREXFRyKJCjKjFDCZRoQvmgKKIa3aIR4zBY89FORp/W/7h2YDM9Hrx1df7AcqZESrPxGGn6BYxpNv1EFviXhoTwj5sQ/kIBaJp/yUUI0HX/7IYm/CIiWP8ojDzrWtas/xkULAefF0wPGN5mAe8O60tocGgfFfWS/Ru/btaSaNrZEzg4ol/RLEJNsA6iWf4kiZASicTncVO8Zbl/XAJlDWX7MB0p2K06sUkZJPYb0amxB79AsVp6zrJFa4RjF09voLSsHlMHh7Nn/317G0qgKKKekaf0Zc2H+zANiW4Jv0Ap/raKr97YQWVpPX2HJzP9giHYYiP7xRX37V6q33mPb577lz+iaVBwND8meAzIwI4Tif9F8DnwJKQEJMKUft8W6b/R+5/NQLWmsW6+e0UiGFJeStWe10gYPxg0HYTeFE+mRV/+fqwShsWNZcfX77Y4fdhhcxNbnJGHVZJozRxC/AcD4wXrv3ivSdQIKCncj5GQQ7ZTY9m39Zw5rg8yIO6CAi94fKBGo86R5d/yHegweCylxCgt43drNuKwWALtHxneT9BkVpP2EgGt6H/WhEAXoCH8mjD4LJpe66JlmY5AE4IEi87lY/I6LdT9fjTHr8g/GhXVHqRdP65/AEUjSqAoop7CbQdxJtMtTrL1NR4WPrEWZ4qdoRMz2LT0AA21Xs6+aUzY+z4Wzrg4Ei+/jBGXfT+idgSpefVJiv/8TxL+vrRd9TXglPCa1CZ9l/wHr7sBoWl+saDpgWMdoVtY+ckSJs8+GQAtWEeIxuNBEjwJiY2yKfjcPIGglK2d82/tlVJiBh5G4zGNx03P/utMmup4pIkpYUFxJRfleYmJ6Zyjq0SquIStUFPjQXOo22G0of4iiqgnPtlB0W4v+Yt3Mvq0wWHtq2DTIdx1Pi67ZxyxCTFUH2pgx6piaivcxCW2Fc8kfAhNw/QZEev/cOIv/gllzzzPwR/OxznvEhzTTkU4EsEavUGuhpxy4THPJy9dwpQpU7rJms7x4Qdfdul6tbjTOrU1Xiyx6nYYbfRsrzXFccGMKyfSZ1gMS175liUvrw9rX5YYvxNkfbU/KaFp+L/SdWtk/6sITUca0SNQAPq99TkJ35nH/t88xJYTTqfo5mMLAEVoMLvi5dpDEnd3N+5aL7Y4JVCiDSVQFFGPxaoz72cnM/rUdPI/L6WqtD5sffUbmUxSVhz/fXQ1/310FbvWlTB+Vj/scZH1QRG6BmZ0CRThiMdx5pUMePkFHNkxpN7718ZzshOxUhRtoyPxdkGgSKEESmt463w4Ivx/XHEkSjIqegRCCOKTHUB4ZzMsVp3zfj6BNR/vpbq0ntMvH07eiVlh66+9CF0/YolHSok0Tf/DMNBiYtAisJVXzxyArW86hdef19L51TCxJMRiur0Ii07qz/8P29Qzu92+3oQuwde1CRQlUFrBqPMRFx/6AHaKrqEEiqJHYBomyxfuIntoHHGu8PqC2OOtTPtux3xd/nLdZR0ORGZ4vbjraol1JbZZV9bVk1dYxorX/9tY1mKLbk0t9jmzGH3XbztkQyjQ4hLIen7REeXSNDGLCxDOFIy9myi+++f0eU0JlK6QVHGIDR9/RrwmICkpsJMLRGAyPLgLpfGjGNxBFJAl3sIyrEJnc305aBqaEAihITSBD0GDEDidEoSGDGxIlhLMZspTBGZwRLOdWv5uA/u+GpeRgq9l0JSWNga2o7fcRt58u7k4creUEI3v5Yg6h29Vb7yu+bZ50aI8eCzrDVxOJVCiDSVQFD0CoQmsNonP4420Ka0ihMZNf38xYv3v/Nfz1G7ZHLH+W0NoGnpmf/+LjL7+9YWoJvpdSC9797947XYqTZOqwUMDpcEt0cGX/p1DTbvLm4TEOMNEk5KtWqBKMHYOklqfgbekmLi4BjZ999yAsPGLDI2WUWhlMMYNjTKk2XOgvJkoaLlLXAbqtozI0rQDquUm8yPrtHL9EdvWj6wjj6jTtCN+iDuVROWDEnWov4iiRyCEYMp3hrHklV188PQK5lw3GdHT446HFBHV91fp8/WAOPHRbh8kml7GP/AIjoyMsLTv/voDKl/6OxfNvDgs7UcjDbVeFrz1BXEJ0bsD7XhFCRRFj2HUqf0pL6olf/FBaircOJPVF0oLojmGuenrAaHuo3j8goTbRCl7wExXaGmo9c/K2pSTbNQR7d8YCkUjQggGjc8GwOeJrh0tQGRz5YTpnuI23NT7QrBryvB2Olnghv2V/Oil1XxvwXJeXbk3jOPcQ27M4Yy01jwU7nFCUKBEeqee4kiUQFH0KAyvX5j4PNG1jVUIgWn4Im1GyDClyaMrH2XaS9OY+tJU7vjiDtyGu/MN+rydWuL5tqyWi55expaianRN8Os38nl26Z7O29FNmB4D78FapDfUn1MZXoFSfwiqCsPXfhTirvX/v7UrH5SoQ/1FFD2G2ko37z+9hvhEjdS+8ZE2pyVCYPh86JFKJhfiSYW3d7zN85ue5+ZxN+OMcfLYN4/Rx9mHm8fd3DnzpNmpJZ431+zHqmss/NF0YmMsjLzrA+59ZxNXnzSwU3a0YWVIWqnfUMqh/2xDug20WAvJlwzHPiwpJG2HfYnHYgfr8ZU5vKHGH5RRLfFEH2oGRdFjKC+sxfDqjJ0xOOqSevlnUKJv2amzLCtcxri0cdw49kYuz7scr+nlb+v+1vkGzc6FMDUljUnzIPq9RMw6L4de3Yp9SCJp14/Bmh1P6TMbMN2hmV0TMswzKDHxSJszfO1HIQ2VVeiaD2sgirQielACRdFjyB6WRNYQK0vf2MHu9cWRNqcFQtMwfBHcAu1Plxuy5jJiM/i26luK64qp8dQAYBFdmHCVZqdE5XfGZlPrMbjo6WXc/NJq6r0Gvzozt/N2tEFX/Vu8Rf5lnYTZ/bENcuEYnQpA3dqSUJjnjzmih/FGGmXCvztwV9Zgj+k9y7O9CbXEo+gxaJpg3s+m88bDS3jvqW9IrHsZjYYOt+OPkNDxL+Km65ricQbL3N4GjAY3uDrcbFRyRd4VvLfrPc5840x0oRNvjee5M5/rdHuykzMoQ9LjeenaKTz12Q4OVNRz59l5XD09HMs7/nuzNM0uCQA9xQEC6taVkHC6Hc/eagDsQ0O0xGOaYXaS1UBGl39XuGmorsdmi/a5ueMTJVAUPQpd15hz/RRe/M0ypv3iMQaNS4+0SQC8cfXl6JH+jgvhfSsjLoM3vvMG7+95H6/hZfaA2WTGZXa+Qdn5G+ukAck8d9UJne+7nWj4HZ21LggUi8tGwox+VH28l+pPCwBwnTMIS6i2xEuJsITxa1vTon8dLcQ0VDdgd0TaCkVrKIGi6HHEJsQAkurCSogSgSIIOIJ2EcNrcqiwlvhkG44O5gYJ9e7bRHsilw6/NDSNmTLqVw+EBtLwAl1LpZAwsz/2vBS8hbXE5MRjzYwLjYGAME10PYxf20KL7ng6YcBd68Ueq/xPohElUBQ9jqXPrUIgGTg5J9KmNOHz4S0sgqzsTjdRtLuS9/+aT12VB00XnHjeEMbO6Nu+i2X0CgCzppLSxx9ARPnuEI/XCAiUrhPTJ56YPqHdaVZVUIBWU42wtO9mml+Sz5/W/ImDdQc5JecUfjT+R9j0NsSXCMTAP45oqDdJSVRTKNGIEiiKHoWUkq1rKxk4NJaE1Oj5UrGkpGLU1nb6eiklHz+7CWeKnTNvGM2Obw7y5X+2kz00kbR+be+q8HvFRIdCaVjyFnWL3kAKKw2bt2PUNeA690wSbuj+RIYdoc4jsTqidwfL5iuvQgwZ3C4fmeK6Yq5bdB39nP2YnDmZl7e8TI23hrun3X3Uaw7eeA7ugmISZpza6vkGr4HNokXdDrquEmPT8NRHZ46v4x0lUBQ9CiEEw8YmsGltLc/86AOGjk9hxFl5pGRHPi5KV3aAuOt8VBbXM+XaQWQNdpHSJ471n+3ji9e2cd4vJraj8+hwbPR88xHFD91P8k0/QZhuEm+6Cz1rQKTNahfxdh0RzuWTLlJvsXDa00+3q+7igsW4fW4WzFmAM8bJlkNbeH3b69xxwh1Y9dbjfXhLysl57RO0uIQW5XvL6rjl1TWs2VtBRoKN+787mlkjwpMLKBK40mM5uKc60mYoWiF6/zcqFEfhlOsm03dNMQXLd7P5m0OsX7mCxDgPk84bwdBpfdEikJSuq1E6bA4LjoQYtq88SN+8ZLatKAJg3Mx+7bpedm6TTEgxDmyn8M7byP7Li1gHj4iwNR1ENu3MilZ83vb/yrdqVkxMar21OGOcTTl9j/UWTQnakbMzP35lDRV1Hh45fwwfbizi5pdWs+SXp5Pp6h25sFx90ti2vgEpZa+bHerpqDgoih6HrmsMmZTJ6TdP45onZ3HW9SOIjbfw8b928O9bP2T/5hDFnOgAfifZzgsUoQlOuzSXbzeWseDnX/DFq9sZdUofBo1La9f1Ec0DBHg2fM2+qy4m/Y77ep44AfC5oz4GSHx8+51tZ/SfQaojlcvevYxrP7qW9SXruXHsjVi1Y0VLlQit5W/Wynov6woq+NnMYVw0uS+PXTQWj8/kV2+s7+S7iD5cOal4DSv11WqZJ9pQMyiKHo1u1Rg0IZNBEzIp2lnBkn+u5H9PrOG826eQ3r8bg5KE4N42aHwaV9w7jaKdlSSkOcgYkND2RQGkaSIimC340J8eJOPO32A/5ZyI2dAlfA0gonsnh+zAhywhJoEXz3qRBRsWUFxXzF3T7uL8oee31cER6QhiY3TiYnRWfVvOvHHZrN5bDsCsvOjYPRcKXOl+5+3K4rrADkFFtKAEiqLXkDk4kfn3nMHrv/mE/z2yjIvvP534pK5tGW0vAhESkeJMtuPsTMwM04BwRhhtA5ndlw/veRRz9HONZcHhaD6309YQHXUeSIJXi+WiP77cti1SgpSYpok0DKRpIg0fUhqYhs//2udGej1IbwPS14BRUYQho3sGpaNkxWfxf1P/r931pZRHfIasusats3O5751NvJdfyKE6D6cMS+PyKf1DbW7EcAWc7SsPHCJrSGJkjVG0QAkURa/CatP5zp2n8uodn/Hh419w/n0zu6Xfri7xdBVpRHYGJeUXvyP7kzOZ/MTb4elASv5w6VzevGUe4BeE8jA503wXkxBN0f+FJgLHIjBBINA0DaHpCF1DaBZ0XafI03tmBTqFpNVlrmtOGsjI7ASW7Syjf0osc8dmR8TPK1xYYnTiHW4qC4qAQZE2R9EMJVAUvY44l41xZw1m2TsFfPnMSk66enK39BtJLxApIytQ1p1/HvHnhHF5Rwh+9so74WsfWH3fPWFtv6uIbviEHc1JdOqgFKYOSgl7/5HClSSoLKqMtBmKw1BOsopeSd6p/YmxSravLuvGXiP4q9IMc5bbVqjZv48d//4Xy+fNBYeD3F/8qlv7VyhChSs9jsoylTAw2lAzKIpeh+E1WfLPlXi8gklntW+bblcJphCMFFKaaN0gULY/+UcOvfFftBgrwuFAz85m2AMPkDRqTNj7VijChSsnjR0batVW4yhDCRRFr6KuysM7D31OWTmccckQ8k4LT+bbI5Ac4RPRHNMwkD4vui08sSOkaR6xAyPUbH92ARXvvc+EjxZhtXWP87GiiY7s4lF0DFd2Mh7fAdy1Puzxx9qKrehOlEBR9Br2rivio6fXIgTM/8UJZA5JbjznM31sL9+Oy+YiO77z+XKORms/uuoOFrHyz09ycM8uvD6v32FTCIIhwZwJibgysrAnJODtO4Ctdgd1pkldSTH1xUX4aqpbdiAl9rQMfnbdDTSYJknOprDsUsqwhLqXUtLQ0MAb/3yejA/e4dQ3/tsrxYmUEsPr5cCe3a2eF5rmH13/H7HxWAA0OxfczSU0DU1o/mdNA0HgtUAILeCk2+xYiIATr1p1jwSudP9OnoqSOjLjuzE8geKYKIGi6BV43QaL/r6WBJeFc247mThX0010X/U+bvr4JvZU7QHgwmEX8pupvwn5VG5w/sRTW8POdxay8q3/MGHWOZxwy604UlJb1DW8HkrXr6Ni21bqDpWxZMVKGoYNZ0RONskTJjIgJ4d+qalH2PjP11/nvkceRDNNYp0JXHXtDWQlJ4NpQgd2VuzYvI3NT/wJs6oSTUqkEIDAdNghKxst3onctBHhcWNarFTkjWDTD3/MrLjQZeaNJqQ00b/dxvsL/nrkueA/UtL4V24+YyabnmXwuXlZ4DoZbChYFmwjUO4uLSYm9eg7iRxOC3uuuBAaJe7hVh7t79++KLleM47v/35o83fdxnVhir57zP+X4pgvjyw4fPv/4df7XyeYMcBjVH5bROZAJVCiBSVQFL2CL/65Eq+hMeun01qIE4DfrfgdXtPLs3OeZWv5Vh5e8TCjU0czf+j8LvfrKSigbMEzeHbuYt3bb/D5P/6MQJCelcMFv3+S2JzWsxHr1hgyJk4mY6J/h9GyN99jWHIic0898Zj9XXvBBXDBBQB8vG49f3n4PvpPP42xbjcxWtv/nQ3T5NNX/0vtO/9j+G/uZPjwYS3OV1VWsX/3t9RWVJJ749U4ExMBWLhmHfuKu9PhuHuRpiTWbuea+x6JmA1/vf4Kbnqifbl2wsGbP5kHv9wemc4DsWsCL5rKOvv6iPZaad80G1/HALF3rqRyfwmQG4I3pAgFSqAoejx1VR625NdwwpwckjKO/IWfX5rPhbkXMilzEpMyJ/Hwioe566u7uixQfNXV7L7gAuJPPpnc4aOoSU9l5l33EZOY1OG2dNHxTaQzx45hyrCHeP39d1m/cjm5dQZbd3yLrKoCIZAIjNRUNIcdGRfPGT/7MZ8/9kcEgjMXPI3dfqQ/TIIrgYRxo48o7+3eD6bPF/Wh7ns1gaWzSOJK0tVW4yhDCRRFj+bgnko+/fNyrJpk5MwhrdYZlDiIz/Z+xnlDzmNb+TYAbhp7U5f6PfTvf1PyxJMknjefjNtu61Jb4P9uNs2OZyR2Ouxcdd75yPnnsXzRp+QOGsiwIf5gU6ZhULS/kLq6Wkq37+KLK6/BVl3NzPcWols6/l+/N9++vR43WiuJ8o4revMfuB24MuIo39v9ebwUR0cJFEWPZfNnu/j01T3ExZjM++VUHM7W82j8ctIvuX7R9cx+YzYA0/tM57ox13W63/oNGyh58k8Meud/WNNDE31UIDC7sE9ZCMHU2TNalGm6Tna/HACGDM+l9sQpHKqs6pQ4iWwqwvDjdTcg9Mg5qMpOiFNFaHH1SWPPRjWDEk0ogaLosRRtLCTW6uX7f5xzzNDbeSl5vHveu6wsXInL5mJCxgQ00bGbkWfPt1S9/x4Vb76FWVdH9iO/C5k4AX/ERDPMMiAuJZm4lOS2K7aCV4IvAj+xTcPENCSWmPDObnjdbvQIzqD4Z3AivIOnt6vQNnBluWjw2nHXebHFqq3G0YASKIoeS3ymC8/G2nblBUmISWBG/xlt1jsco6qKXfO+C0gcI0eR/stfkDBrVseNbQNNE8iuTKGEGR3Z7WGn1368lxXv7MbrNhg4JpUZV47A5gjPV5ZpGBFNFeCuq0WLYLJHBbjSAkkDi+tJH6AESjSgBIqix6JbdWSYMtAaNTWUPfscFS+9RNLll5P2o5vD0k8QDRH2GZSu0p23z31bDrH09R2MPi2H5KxYvn57F1+9vp3Tv5cXlv6kaUTUSdPn8SL0CH8dH+8+KEGBsreQ9AEJEbZGAUqgKHowtYWHsApvSNoy6+spf/116ld+g6+kBPeOHTjGjyPn6aeJHXPkrpZQIwRd8kHpDrrz/r130yHik2ycfPFQhBB8/vI2Ni0tDJ9A6WQmaiklu9eVcnB3FSk5cQyZmNGpTL+mzxvSVAWmYVK6rwarTScps3fGrgk1tlgrdpuPyn0HUVuNowMlUBQ9FndFDZo0On19/ebNFFx3PZgm0vBhHzGS2MmTcM6ZTdz06VgCMUC6AyFEp2+S3UF3WxbnslFf7aWyuB5nih2rTcfr7vzfuk1M2SkBtvT1Haz7pID4JBs1H7rZs76M2deM7HA7hs8XsiWmmnI3//vTWg4dqAVg8IQ0Zl0zEr0TTsD1HoN739nE+xsKSYqN4eezh3HumNBHYo4WXElQebAq0mYoAnTpf8TDDz+MEIKf/vSnjWU33HADgwcPxuFwkJaWxrx589iyZUtX7VQojiB9whDqcWD4Or4DwldeTsE115J1z90M+2opucuX0//ZZ0j74Q9xnXNOt4oTCMRBiWKBgoSOR2rpPMNPzMKZYufle5fzzC+/xPCZzP3J2LD1539nHVModVUe1n1awLT5g/nBQ9M55ZJhbF95kD35pR3uP5QCZdlbO3DXepn/8/HMvGoEO1eXsObDvZ1q6+H3N/PWmv18f9oAhmXE8+OX15C/r/fudHGlxaqsxlFEp/9HrFy5kqeffpoxY1pmMZ04cSLPPvssmzdv5sMPP0RKyezZszGMMP76URyXpA5MQaJRcbCu3dd49hZQ9NBD7Jw9h+SrrsI5c2YYLWw/QoARzQIF6E4nBZvDwoW3T+Lki4cxfnY/Lr7zBPqNSAlbf9IwOpz6oKHWCxLS+/tzIiWmxwJwcHfHf4GbIRQoJd9WM2hCOtlDk8idkgnA8oW7jn3RUT57H248yPdP7M+ts4bxl8snIiWc/9evQmJnNOLqk0JllXKQjRY6tcRTU1PD5Zdfzj/+8Q/uv//+Fueuv/76xuMBAwZw//33M3bsWPbs2cPgwYO7Zq1C0YzUvvHoGOz6ag8pF446Zl2zoYFvr7gCX0kpjrFjGPTBB1g7ueU2HGghnp+or99HadlnWC0u0tLmoOtdS/AXCekUY7cw6pQ+3dKXYXRcICRmxJKQaufL/2xn9Gk5bFlWiD3eyoQ5/TvRvzdkAiU5O45v80s5dEofasobABhzes4xrzG9Da1uvU9wWNhTWouUkpJqNwBTB4dPKEYaV1YSdR4HngYfMXblARFpOvUXuPnmmznnnHOYOXPmEQKlObW1tTz77LMMHDiQvn1bz0nidrtxu92Nr6uq1Pqfon3E2C30G2Bly9J9jJmWSM2HH+KrqMQ+bCiuuXMBOPjY49R88gm+0lISzjqLrN/eE1mjj4ImBGaIZlDKy1ewdt1VSGkipQdn/EgmTnwFXY/tdJsyyncYdRX/NuOOzaBomuDsm8bwyfObWfzvrSRlxXHOD8dgtXV8v5PpM0IWB2Xqdwfz9h/W8PJvlwPQZ1gi0+Yf+8eh4a5Ha8VH5ebTh3DLK2s547HPKatxk+Wy88TF40JiZzQSzGpcWVJPWl9nG7UV4abDAuWVV15h9erVrFy58qh1/vKXv/CrX/2K2tpacnNzWbRoETExrUf5fOihh/jtb3/bUTMUCgByZ+fxwd83suXy60keMQAtwUnZl19y8KGHQQiEzUbO449jGz0qquNMCEHI4qDs3PV7nM4RjB/3PHV1u1mx8jts23YfeXkPhaT93ohpGAjR8c9HSp94LrpjMqZhtnqDby8+rw/RweCBRyMxPZbLfjuVA9sqsNp0sga72hRfhrseSyv2zxvXhzSnjQ82FJEYG8MVU/uRFNf6d3lvIDHNL+IrDxxSAiUK6JBAKSgo4JZbbmHRokWtJhoLcvnllzNr1iwKCwt59NFHueiii1i6dGmr19x+++3ceuutja+rqqqOOtuiUBxOWj9/vAL9N0/Rd+agCFvTeTShYcrQhDtvaDhAZuZ8dD2W+PgRABwofE0JlGNgdsIHpTldESf+/n0hDbVvjdHpP6r9SzGm131UAX/i4FROHJwaKtOiGlucBZvVR+XeIpjS8aU6RWjpkEBZtWoVxcXFTJgwobHMMAyWLFnCU089hdvtRtd1XC4XLpeLoUOHMnXqVJKSknjzzTe59NJLj2jTZrNhs3VtfVxx/JKQ6qB/P41v3t7GqJ4sULTQLfEkJU7hwIFXiY8bRm2tPzni2LELQtJ2b8XshA9KKJGGL6LJCutrqimp8ESs/2hBCIEr0aSysCLSpijooECZMWMG+fn5Lcquuuoqhg8fzq9//Wv0VhS4lBIpZQs/E4UilNhjdSyWnu0jEUoflKFD76Rhw4/ZuOlnCBHDwAE/ISX51C62Knp1oFFpmhEVKIZpdmkGp6tInxeLJcK5gKIEV6qNyrKaSJuhoIMCxel0MmpUy90ScXFxpKSkMGrUKHbt2sWrr77K7NmzSUtLY9++fTz88MM4HA7OPvvskBquUASJTYqjflsdUsqIfsl3hVAGaouJSWHihJfweErR9dguOce2IOq3QXcew9e1JZ6uIiMsUCxWCxnJR1+2P55wZSVxYHf7QxcowkdIJbPdbueLL77g7LPPZsiQIVx88cU4nU6++uor0kOY+VWhaI6zTxIes2fHLvDPoIS2zZiY1NCJE3p3slspIzuDgozwPilpRjQXUTThykmjtsGB16Nid0WaLm/0Xrx4ceNxdnY27733XlebVCg6hN3p92F6485FjJ8/ksGTuyd2Rijx+6CExkk2LIjenUvO8PlCmgunM0R0BifC2ZyjCVe6P3dRVUk9KX3iI2zN8Y36RCp6PENOyOKMSwdhmvDBgq189tfl0R02vhX8u3h6ls29CWn4EBF0Uo3051VKg94tQduPKxARuPKg8kOJNEqgKHo8QgjyTh3AhQ/N4oQ5WWxaV9uh8PfRgNC0KPfxEFFuX9cwTRnSbb4dRcoIO8maZocD1fVWHE4rVt1HZUFRpE057lGxfBW9BiEEg6f2Y8WHhVQU1UYkzbzH8PDi5hdZV7yOoUlDuXLklcTHtD1NrGkaRhTf/w2fl+I9u/jwbxvwr/dIkIEbmpA07vIRAiEEAuEXXQKE0Pw3X61ZOQIhmi1rBJ6F0PztaE3lwfZGnTEbZ3J4wqybhi/CDtYRThYpzV6+T6v9CCFwuXxUHjgUaVOOe5RAUfQqEjNiseledi3ZzsBx3e+YfceXd/Dp3k+ZmDGRf236F8sLl/P8Wc+3muekObomkFHsgyJ0HU3TsDv8YuvwW6mgKaSARILpf5amRJpGIOw+IM3GG7GUssk5tHlZi3MSJGz6ZgVLl68guU8fpOkPvS8D1zbWlTTWDz4HLW28+QfPHdZnfU013vo6nnrgXr9I0gSaEGiahq7rWAIP3aJjsViwaP7j4Dld18mPT0ZaYgIzEQKhBcSVEAihoWkBEdI4eBIRsKFuTwGUlPDi/xa2GNPGuqJ52eG5lwXS5yW9cD8uaUJjH6Y/OrEEs7YWo6oSS0ZGs/NN41BbUYzv4D7Kf//TQLnw2+etg9oSSOofEJEtBWVQQDaWiZaWoTVdI/yKtFndw9uC4KR+02xOs7YOF5CtCspWykRrbR1+0PK6OE8GFYW9N+dQT0EJFEWvQtMEGpLtm+sZs7eqMdJsd1BcV8yHez7k3hPvZf7Q+Sz6dhG3Lr6VN7e/yfnDzj/mtULTMKJXn6BpGqn9+nPqmZHJ/uz913OYhsmYE05AQ0PT/bMymq6hCR2hgdB0NBGcuWkSBn4H3+CMTbNZnWZCAtkksEzDh2kY+LxePB4PXo8bj9uDx+PB43bj9Xrwerz4DB8+nw+Pz6Corp43EuL5XoK9SahJv0CQSExTNmZ0l403egGBWSbrwKE4XEn4rH6H79bmUlqUiZaFO8qriC8s5ez0JH+BJhDCChb/ezWlieHzYY13Nr1naBQVsUlJJPdLwRLnCOgT/5jgq4N6F9KZSdM2s2YCTx5+LJtWAg873zRDJJuldTj8euNIAdWiXmufjsPaanF4rLJWGgvYGGs6+bZM7TyNNEqgKHodJ182nI/+tYvdy/aQ1m9Mt/XrMfyROBNsflEUZ/UvMZW7y9u8VpgG+w4V88ePPqa/zYphmpimiSlNTBNMKf3HEszG2Qj/DQECPgyNZYE2afrV2rj8Ao03cA3hv7GjNf3yDdzMm34N+/0TthUdRIuLXG4SXdNITEpm6IhjZ62OFN98W8CSXfu5fsrEiPT/yderWBfnYtwFcyPSf28jY/FeNr+yHcNroluVq2akUAJF0esYOn0Aa97eQvH2km7tt098H8amjeW+Zfex+uBqPt37KTnxOXx/xPfbvDbr0EGGblrBjhgLdqcDTdPQGpcaNP9ygxBYhUBrMQOg+SWKsPj9WIPigqBWkc1+0Tf7NWuaGFJiBsqDSzQ0WxoJLj+gaSQX7ydZGsC80A5au4mwj0Yb1JkSRwT79wmwmFE8BdfDSMz2zzRVldVHxJdN4UcJFEWvJHtEKltWlHVrdFkhBE+c/gSPfvMonxV8xrCkYfxi0i+I0dvO/hqj64ywx/Ljq3/QDZZ2nG/eeYt9m/LbrhgmhIjuXUS1hokjgqHWfBKsvTqUXvfiCmQ1riiuUwIlgiiBouiV9Bnfn3VfV1G2v5bUnO4LtpTiSOGhkzueNVjouj+aZ5SiRdiJN+gSEa3UmhJ7JAWKEGihDkV8eB+mj1UHV+E1vUzOnIxN771JXuNcMegYlO8qYeCYtEibc9yiBIqiV5I1JBGAj/+8nEsemhFZY9qBpmmYYb7BdAkhIjqB4c9VFL0CzpASSwS3KXsRYZVHNZ4arv3oWjaWbQSgr7Mvz855loy4jDD2GjmEJoi3+yjfq7YaRxLl/aPoldjjrDgdBmXlgjUf7KKh1htpk46NEEQ4G8sxEUKL6AxPKJMphgNNCCIpn7yAFsbx+dfmf7GrchcvnPUCr899nYLqAm757Jaw9RcNJCRZqTxYG2kzjmuUQFH0Wr77fydh07189dYe/vfgEipL6iNt0lGpra5id0n0Rq4UWmQFgiY0zGh2Ao1wsr9YQVgF0s6KnYxMGcn49PHkJucCNM6m9FYSs+Kpqoriz9xxgBIoil5LQoqDq56cxZwrh1JWZvLib5bx2u0fUVUWfUIl3pVI/5TojbugaXpEBYrQolugRDoGq054Z3BGpoxkXck6Fn27iK8OfAXAjH7Rv3TaFZIGplPntWJEc4CiXo7yQVH0anRdY8jUvmQNT2ff5lKWvbSe/96zmFOuHMfA8ZlRk38kGM49FNRVeSjZW01iRiyutBBtftU0ZBcEgmmYLF+4i81fFWKx6kw4sz+jTml/1mlN0zB80btMpwW3eHeS+vr9eLylOOOHo2kddz7VwzyDcunwS1letJxbF98KwKiUUdwz7Z4w9hh5EvsmItGoLmsgMZBAUNG9KIGiOC6IS7SRO60P2bkpvPfIEt7/x2biY9aRlhWD4ZPkzshl4KQsrDGRyWgbqrmJnauLWfTsJgyvCQKmzhvExDMHdLld0ezfzrBm0V7WLCpg7Iy+1Fd7+PylrcQn2RgwOrVd12u6hukJ7S3YbPBR8+V+vMV1xPRPIH5qVqcTBmp0TiBIKdm+/X4K9j0HgM2WxbixzxAfP6xj/QuBEUYnXbvFzl9n/JVdlbvwml6GJQ1rM31DTyco7itL6pVAiRBKoCiOK5zJdi5+eDaFOyvIf3s9FUV1mBIWvbAN8cIWXA4vaTlxZI3JITM3jeQ+cegRzHLbEQyvyWcvbqH/qBSmnz+E/MX7+PqtXfTNSya9f9dC/vvjkHReIOxaW8rQSelMP38IUkq2fl3Eu39ez81/O6Nd12shXuKRpqT0mQ14i2qx9nFS+e4uvAdqSb6wY8IgiBACsxNLYIfKl1Kw7zmGDLmNRNdk8vN/yJq1P+Ck6V91KH6PLsQxk002NDSw6tMlCGQg7L9oDPXvfwME0gNoLXPjNObaCTwHTq0WX/vzCwkBmt9HKBi5WAvkMUKIxvIWbTXLwyOC+XeanwuWNysTmkDTdHRdQ9N0f4qD4GtdR9c0hO5/bQme1/UuxUCKT7KjYVLxbRn9R6q8PJFACRTFcUnW4ESybj2l8XV5US37NhykcN0+SvbVsmP7LiR70DBIijdI6+ckPS+L9CGppObEhzz8tf+LtGvzKDUVbtx1PkaelE1CqoPhJ2ax9uMC1n+6j5lXjeiyfV2xzubQqSptwDRMvIGZkPik9i9lCE3v0hLT4Xj2VuHZW03qdaOxD06k4p1d1Hy5H+fJfbB2IjCXrmkYnRAo1VX5WCxO+vW9FiEEuiWWurrdHb6x6hx7Bmfr2g1UPv00cvbsZskVm+W3CebCaf4emuXX8efh8TsCi2b1myd8lM3q+vNCms1S6vjriWb9imDUYhk819hxy76DuXlMw2+HEcjXY5r+hzQRhv8Zw0RIf7lo7fMi/Um4Dx9dKURT5GSC+ZJAt89l775Kxh5z9BXhQgkUhQJIyowjKXMQo2cOAsDrMSgtqKFoUyFFGwo5sLOKrZvqA6LFJCneR87IVMbPH01cYggCVoXAATU+yYY93kr+5/uJT7azcckBAMbP7tfltuliJNfxs/vzvz+t4993f43XbRDjsPDdW8e3+3o91DMoAZGkx1sBEAHBadb7OtWermmdciKOixuKz1dN0cG3SXRNxjAa/PZ1MAKyJgRGG0tw3sknMO/mGzps4/HMPx/7hoM1kbbi+EUJFIWiFawxOlmDXWQNdsHc4QD4vAZl+2o5sLGQwvwDbFpRxpZvFvO9R2dgc3Txv5LouousbtE44/t5fLRgIy//djlCE5x04VBS+oQokm4Xpsv75iVz/q8msnV5ERarxsiT+3TIgVfooQ1kFzMgAT0hhrIXN2MfkULdqoPEDEggZkDnlsIsWueWeFJTzyA9/Rw2bfq5vx1LApMmvt7xGZQ2nGSjxRm8p5GU5qBwa9vJPhXhQQkUhaKdWKw6GQMTyBiYwPhzc6kqreff//clK19dx0lXhiCLbQjuvwPHpPKDB0+kdF8NiemxHVpGCTcZAxLI6KQA8G9zDt0Mihajk3rtaCre2UX9uhJsgxNJnDuo0z4LWid9UITQGDXyCar6XYPHXUJi4iSs1sSO9w9U19awYdVapDT9ySENiUQiDZPibds63KYCsjLjObC8GGlKJfIigBIoCkUnSUh1MHJiIptXlHLi9yVaF77AvKVlNGzdGhK77HFWcnKTQtJWtBDqJR4Aa3osaVePCklbXYkkK4TAldA1L4eGlBS2mho7/veuX2RpAoIOrwFn0wEzuxa3pLpmC9u23Utt7XYSXRPJzf0tNlvvDHUfJCszFs2Q1Fa6iU+yR9qc4w4lUBSKLjD0jKHkr1rNxk92MXrW4E63Y0lJxj48N4SW9S78SzzRGzBL66ITcZf7j4unavxEvnv9ZWFp3zDqWLv2SmKsyeT0uYIDha+xPv+HnVqO6kkEsxpXltQrgRIBesb+SYUiSskanMiwEXaWvPEt37ye3+l2/A6W0ftFH8odNJ1B03RkFCdTbKiv50Bh5FIVhFsgVVSswuMpYdSoJxk06Bayss6nqmotFRUrwthr5ElI9eeoLjlYF2lTjkuUQFEousjMH09j+Fgn33xcRF2Vp3ONRLc+8e8qieAavK5rUZ3NOM7hIDMrK2L9+yPZhk+iWCz+rdcNDYUAGD5/Er2YmN4dH8Ri1TGdFvYVqa08kUAJFIWiiwghmHrpGKy6wf8e/LyTOWtMolmhmIbhD+IVITRNj+olHvDH14gUppQ0HCtSWxdJSBhHYuIJrM+/gZXfnEfBvhfIzr6EuLghYeszWohJtlGmZlAighIoCkUIiEu0ccZ1Eyit0Dm4p6rjDUiiei1fmiZCi9zXha7rndol012ICGczrjNNDnrCl6tICI1xYxcwaOAtxMYOYnjufQzPvTds/UUTCakOasoaIm3GcYlyklUoQkTfQDjs9/60mqnzh/g3UGiaP6y4riE00ShC/BssRGNI77L9klojnb0by5oF3vRH0PS/lk2BNQOFLYN++l/IQMTPwCUgJQ21XmxxFoSmBUKFa/7+NX9YcqEHwpM3Ow6GQhcaaJqgtsrE8DmoKqv3nw/U0QJ1ROM1gXYbQ6mHhmj3QfHv4omcwEyxWMixx4S1D12PpX//4y/QW0ZGLKUbDkXajOMSJVAUihDhrvNHIa2vk3z27+0dvFoDTmT/n9aF3K7QEAecwL/uXNbB6/yCSYiAcBKBEOfBtCtCBtO0NJY12x0b2CILPsOL2zeA5+9eHKgjmkSe1kwoNYqm5uUtRZemC79IE82ElfBfW1XqZv+mKvqOdeJMsWG1WrDEWIixWbDG+B+6RUe3aOgWDc3iF2M1xbU4i0y+3VCGaUq/mGpFTDYPLy+RSDPw3Cy6u/91szKaidXGsPI01jEMk837qhhTXceiXYGt6oHxlAQHF3/KG/8fwL8LWYjAbmT/ewiK1MayxnJ/LiQ9OL56MzEqxFFn/loUi+aHotXyVj86RxS1WnhkUTu0bHuXYvVaA91t0lDrxR5nbdc1itAgZOcWzMNGVVUVLpeLyspKEhK6luBMoehuWtxIms+CyPadM00Z+GL33wCg+UxL0w2m8ebdvPNWvuyFEC1uiqbZ1I+UEtPw30xNQzbeWE0jcM4M3ECD5VIGjv1lwTYa6wTOmyaNx42vG/szMQ0TwzAxfSamaTaWNT5MiWkYyIBN/jITryHRdEuTnWZTHzL4noL2BcfYbLrZ07w8OBtlNo2NBIwGkKZA6KDpBMYCMKNj+c0vOAIvAs9SgGZAbZIVa7OUTo25bWSgalDtBBtq8TqQC8ek8e4uzGbl8thaorcjLYKrH5xObEJ4Z6l6OqG+f6sZFIUihAQzvnY9cL0imggKLsOQfmFlSAxfUHDJxpmZphmGps8CHCYoG8uCnxVaiM+msqb60eCf1FxYB0VhcKYIDpvIaJ5472g/gZsvUQayLB9BO992q8PTSmGrzbWjD13XQp4gVNE2SqAoFApFG/j9iASaDsTokTYnIjTO5CH86ZMVijCjJKFCoVAoFIqoQwkUhUKhUCgUUYcSKAqFQqFQKKIOJVAUCoVCoVBEHUqgKBQKhUKhiDqUQFEoFAqFQhF1KIGiUCgUCoUi6lACRaFQKBQKRdShBIpCoVAoFIqoQwkUhUKhUCgUUYcSKAqFQqFQKKIOJVAUCoVCoVBEHUqgKBQKhUKhiDqiLpuxDOTmrqqqirAlCoVCoVAo2kvwvh28j3eVqBMo1dXVAPTt2zfCligUCoVCoego1dXVuFyuLrcjZKikTogwTZMDBw7gdDoRQnTo2qqqKvr27UtBQQEJCQlhsrDnoMajJWo8WqLGoyVqPFqixqMlajxa0tp4SCmprq4mOzsbTeu6B0nUzaBomkZOTk6X2khISFAfoGao8WiJGo+WqPFoiRqPlqjxaIkaj5YcPh6hmDkJopxkFQqFQqFQRB1KoCgUCoVCoYg6epVAsdls3H333dhstkibEhWo8WiJGo+WqPFoiRqPlqjxaIkaj5Z0x3hEnZOsQqFQKBQKRa+aQVEoFAqFQtE7UAJFoVAoFApF1KEEikKhUCgUiqhDCRSFQqFQKBRRR68RKKtXr2bWrFkkJiaSkpLC9ddfT01NTeP5srIyzjzzTLKzs7HZbPTt25cf/ehHvTbnT1vjsW7dOi699FL69u2Lw+EgLy+PJ554IoIWh5e2xgPgJz/5CRMnTsRmszFu3LjIGNpNtGc89u7dyznnnENsbCzp6en88pe/xOfzRcji8LJt2zbmzZtHamoqCQkJnHTSSXz22Wct6nzyySeceOKJOJ1OMjMz+fWvf31cj8fKlSuZMWMGiYmJJCUlMWfOHNatWxchi8NLW+Px3HPPIYRo9VFcXBxBy8NDez4f4B+XMWPGYLfbSU9P5+abb+5QP71CoBw4cICZM2cyZMgQli9fzgcffMDGjRu58sorG+tomsa8efNYuHAh27Zt47nnnuPjjz/mxhtvjJzhYaI947Fq1SrS09N58cUX2bhxI3feeSe33347Tz31VOQMDxPtGY8gV199NRdffHH3G9mNtGc8DMPgnHPOwePx8NVXX/H888/z3HPPcdddd0XO8DBy7rnn4vP5+PTTT1m1ahVjx47l3HPPpaioCPAL+rPPPpszzzyTNWvW8Oqrr7Jw4UJuu+22CFseHtoaj5qaGs4880z69evH8uXL+fLLL3E6ncyZMwev1xth60NPW+Nx8cUXU1hY2OIxZ84cTj31VNLT0yNsfehpazwAHn/8ce68805uu+02Nm7cyMcff8ycOXM61pHsBTz99NMyPT1dGobRWLZ+/XoJyO3btx/1uieeeELm5OR0h4ndSmfH44c//KE8/fTTu8PEbqWj43H33XfLsWPHdqOF3Ut7xuO9996TmqbJoqKixjp//etfZUJCgnS73d1uczgpKSmRgFyyZEljWVVVlQTkokWLpJRS3n777XLSpEktrlu4cKG02+2yqqqqW+0NN+0Zj5UrV0pA7t27t7FOe75jeiLtGY/DKS4ullarVb7wwgvdZWa30Z7xOHTokHQ4HPLjjz/uUl+9YgbF7XYTExPTIjmRw+EA4Msvv2z1mgMHDvDf//6XU089tVts7E46Mx4AlZWVJCcnh92+7qaz49Fbac94LFu2jNGjR5ORkdFYZ86cOVRVVbFx48buNTjMpKSkkJubywsvvEBtbS0+n4+nn36a9PR0Jk6cCPjHzG63t7jO4XDQ0NDAqlWrImF22GjPeOTm5pKSksKCBQvweDzU19ezYMEC8vLyGDBgQGTfQIhpz3gczgsvvEBsbCwXXHBBN1sbftozHosWLcI0Tfbv309eXh45OTlcdNFFFBQUdKyzLsmbKGHDhg3SYrHIRx55RLrdbnno0CF5/vnnS0A++OCDLepecskl0uFwSEDOnTtX1tfXR8jq8NGR8QiydOlSabFY5IcfftjN1oafjo5Hb59Bac94XHfddXL27NktrqutrZWAfO+99yJhdlgpKCiQEydOlEIIqeu6zMrKkqtXr248/+GHH0pN0+RLL70kfT6f3Ldvnzz55JMlIF966aUIWh4e2hoPKaXMz8+XgwcPlpqmSU3TZG5urtyzZ0+ELA4v7RmP5uTl5cmbbrqpGy3sXtoaj4ceekharVaZm5srP/jgA7ls2TI5Y8YMmZub26EZ2KieQbntttuO6ngUfGzZsoWRI0fy/PPP89hjjxEbG0tmZiYDBw4kIyPjiJTPf/jDH1i9ejVvv/02O3fu5NZbb43Qu+s44RgPgA0bNjBv3jzuvvtuZs+eHYF31jnCNR49FTUeLWnveEgpufnmm0lPT+eLL75gxYoVfPe732Xu3LkUFhYCMHv2bH7/+99z4403YrPZGDZsGGeffTZAjxmzUI5HfX0911xzDdOnT+frr79m6dKljBo1inPOOYf6+voIv9P2EcrxaM6yZcvYvHkz11xzTQTeVecJ5XiYponX6+XJJ59kzpw5TJ06lZdffpnt27e36kx7NKI61H1JSQllZWXHrDNo0CBiYmIaXx88eJC4uDiEECQkJPDKK69w4YUXtnrtl19+ycknn8yBAwfIysoKqe3hIBzjsWnTJk4//XSuvfZaHnjggbDZHg7C9fm45557eOutt1i7dm04zA4boRyPu+66i4ULF7YYg927dzNo0CBWr17N+PHjw/U2QkZ7x+OLL75g9uzZlJeXt0gbP3ToUK655poWjrBSSgoLC0lKSmLPnj2MGDGCFStWMHny5LC9j1ARyvFYsGABd9xxB4WFhY0CzePxkJSUxIIFC7jkkkvC+l5CQTg+HwDXXHMNq1evZs2aNWGxO1yEcjyeffZZrr76agoKCsjJyWmsk5GRwf333891113XLpssnXsr3UNaWhppaWkduia4Zv7MM89gt9uZNWvWUeuapgn415d7AqEej40bN3LGGWfwgx/8oMeJEwj/56OnEcrxmDZtGg888ADFxcWNuxAWLVpEQkICI0aMCK3hYaK941FXVwccOROiaVrjd0QQIQTZ2dkAvPzyy/Tt25cJEyaEyOLwEsrxqKurQ9M0hBAtzgshjhizaCUcn4+amhpee+01HnroodAZ2k2EcjymT58OwNatWxsFyqFDhygtLaV///7tNyqkC1MR5E9/+pNctWqV3Lp1q3zqqaekw+GQTzzxROP5d999Vz7zzDMyPz9f7t69W77zzjsyLy9PTp8+PYJWh4+2xiM/P1+mpaXJK664QhYWFjY+iouLI2h1+GhrPKSUcvv27XLNmjXyhhtukMOGDZNr1qyRa9as6XW7VqRsezx8Pp8cNWqUnD17tly7dq384IMPZFpamrz99tsjaHV4KCkpkSkpKfK8886Ta9eulVu3bpW/+MUvpNVqlWvXrm2s98gjj8j169fLDRs2yHvvvVdarVb55ptvRs7wMNGe8di8ebO02Wzypptukps2bZIbNmyQV1xxhXS5XPLAgQMRfgehpb2fDyml/Oc//yntdrssLy+PjLHdQHvHY968eXLkyJFy6dKlMj8/X5577rlyxIgR0uPxtLuvXiNQvve978nk5GQZExMjx4wZc8T2rk8//VROmzZNulwuabfb5dChQ+Wvf/3rXvtBams87r77bgkc8ejfv39kDA4zbY2HlFKeeuqprY7J7t27u9/gMNOe8dizZ48866yzpMPhkKmpqfLnP/+59Hq9EbA2/KxcuVLOnj1bJicnS6fTKadOnXqEM/Dpp5/e+P0xZcqUXuksHKQ94/HRRx/J6dOnS5fLJZOSkuQZZ5whly1bFiGLw0t7xkNKKadNmyYvu+yyCFjYvbRnPCorK+XVV18tExMTZXJyspw/f36LbentIap9UBQKhUKhUByf9Az3c4VCoVAoFMcVSqAoFAqFQqGIOpRAUSgUCoVCEXUogaJQKBQKhSLqUAJFoVAoFApF1KEEikKhUCgUiqhDCRSFQqFQKBRRhxIoCoVCoVAoog4lUBQKhUKhUEQdSqAoFAqFQqGIOpRAUSgUCoVCEXUogaJQKBQKhSLq+H8xR09pcoddaQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "cutCountyList = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotPoly(countyCP[c].buffer(0.03))\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This code block reads in a csv with whole districts to be cut out of the map\n",
      "For WI my input file says to cut out 0 districts out of 8\n",
      "There were no cut districts in WI\n"
     ]
    }
   ],
   "source": [
    "print(\"This code block reads in a csv with whole districts to be cut out of the map\")\n",
    "unclippedMAP = MAP\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "nCutDistricts = nCuts\n",
    "nStops = trimDF[\"nStopLines\"][DFrow]\n",
    "nDistricts = trimDF[\"nDistricts\"][DFrow]\n",
    "stopLines = list()  #the 'stoplines' stop wedge growth that hops across concave map areas (not currently used)\n",
    "cutCountyList = list()\n",
    "allCutLists, allCutPops = list(), list()\n",
    "print(\"For\",STATE,\"my input file says to cut out\",nCuts,\"districts out of\",nDistricts)\n",
    "if nCuts > 0:\n",
    "    cutList = list()\n",
    "    cutXs = ast.literal_eval(trimDF[\"cutXs\"][DFrow])\n",
    "    cutYs = ast.literal_eval(trimDF[\"cutYs\"][DFrow])\n",
    "    cutPoints = [Point(cutXs[i],cutYs[i]) for i in range(len(cutXs)) ]\n",
    "    for cutNo in range(nCuts):\n",
    "        print(\"performing cut no\",cutNo,\"for state\",STATE)  #first two cutPoints must form the cutLine\n",
    "        cutNotDone = True\n",
    "        thisCutPoints = [ cutPoints[int(4*cutNo)],cutPoints[int(4*cutNo+1)],cutPoints[int(4*cutNo+2)],cutPoints[int(4*cutNo+3)]  ]\n",
    "        while cutNotDone:\n",
    "            cutPoly = Polygon([thisCutPoints[0],thisCutPoints[1],thisCutPoints[2],thisCutPoints[3] ])\n",
    "            cutLine = LineString([thisCutPoints[0], thisCutPoints[1] ] )\n",
    "            cutList = list()\n",
    "            cutPop = 0.\n",
    "            for c in range(nCounties):\n",
    "                if cutPoly.intersects(countyGeom[c]):\n",
    "                    if cutPoly.contains(countyGeom[c]):\n",
    "                        cutList = cutList + countyTractList[c]\n",
    "                        cutPop += countyPop[c]\n",
    "                    else:\n",
    "                        for t in countyTractList[c]:\n",
    "                            if cutPoly.contains(tractCP[t]):\n",
    "                                cutList.append(t)\n",
    "                                cutPop += tractPop[t]\n",
    "                            if STATE == \"NC\":\n",
    "                                if t == 1828:\n",
    "                                    print(\"special for NC - include vtd 1828 from county 55 in the cut list for contiguity\")\n",
    "                                    cutList.append(t)\n",
    "                                    cutPop += tractPop[t]\n",
    "            print(\"the total proposed cutPop is\",cutPop,\". Compare to\",int(statePop/nDistricts) )\n",
    "\n",
    "            doIcut = input(\"enter 1 to apply the cut\")\n",
    "            if str(doIcut) == str(1):\n",
    "                cutNotDone = False\n",
    "                allCutLists.append(cutList)\n",
    "                allCutPops.append(cutPop)\n",
    "            else:\n",
    "                print(\"Here is the state and the last proposed cutPoly.\")\n",
    "                plotPoly(cutPoly)\n",
    "                plotPoly(MAP)\n",
    "                plt.show()\n",
    "                print(cutPoly)\n",
    "                oldPts = list(cutPoly.exterior.coords)\n",
    "                newPtXs = ast.literal_eval(input(\"enter alternate [ x0, x1 ] for the first two points\") )\n",
    "                newPtYs = ast.literal_eval(input(\"enter alternate [ y0, y1 ] for the first two points\") )\n",
    "                thisCutPoints = [Point(newPtXs[0],newPtYs[0]), Point(newPtXs[1],newPtYs[1]),oldPts[2], oldPts[3] ]\n",
    "allCutVTDs = list()\n",
    "for L in allCutLists:\n",
    "    for v in L:\n",
    "        allCutVTDs.append(v)\n",
    "if nCutDistricts == 0:\n",
    "    print(\"There were no cut districts in\",STATE)\n",
    "else:\n",
    "    print(\"here are your cut districts\")\n",
    "    plotPoly(MAP)\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        cutGeo = tractGeom[L[0]]\n",
    "        for v in L:\n",
    "            cutGeo=cutGeo.union(tractGeom[v])\n",
    "        plotPoly(cutGeo,2)\n",
    "        plotCenter(i,cutGeo)\n",
    "        plotCenter(allCutPops[i],Point(cutGeo.centroid.x,cutGeo.centroid.y-0.5) )\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4c915415-6c44-4c43-9826-b565cebed95a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write the vtd cutlists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Write the vtd cutlists to a file\")\n",
    "cutDistrictNo = list()\n",
    "for v in allCutVTDs:\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        if v in L:\n",
    "            cutDistrictNo.append(i)\n",
    "            break\n",
    "nbrDF = pd.DataFrame( {\"vtdNo\":allCutVTDs,\"cutDistrictNo\":cutDistrictNo} )\n",
    "outname = STATE+\"wholeDistrictCuts.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "nbrDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "17721728-e5c0-4787-b430-9d7d94970667",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8 districts\n"
     ]
    }
   ],
   "source": [
    "countyPop = [0. for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    countyPop[countyNo[t]] += tractPop[t]\n",
    "print(nDistricts,\"districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f3073320-8d92-45ba-beb2-fb8c08d7170d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed all whole districts.  Finalize stats before squishing in outcroppings.\n",
      "Of the total statePop 5893718.0 we ignore 0.0 as it is cut out of the map\n",
      "This excluded pop comes from a total of 2 tracts\n",
      "Our final adjusted number of state districts, excluded fixed cut-out is 8 rather than original 8\n",
      "Each district will be drawn to house 736714.75 = 1/ 8 of non-cutout state pop 5893718.0 vs original= 5893718.0\n",
      "Here is a county-level modified map with each county's fraction of a district pop\n",
      "working on county 0\n",
      "working on county 20\n",
      "working on county 40\n",
      "working on county 60\n",
      "here is the WI map excluding cut and unpop coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Removed all whole districts.  Finalize stats before squishing in outcroppings.\")\n",
    "trueCountyPop = [countyPop[c] for c in range(nCounties)]\n",
    "trueCountyGeom = countyGeom.copy()\n",
    "countyPop = [0. for c in range(nCounties)]\n",
    "trueStatePop, true_nDistricts = np.sum(trueCountyPop), nDistricts\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "# minTractPop = 4.5  #already defined above\n",
    "populatedTractList = list()\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "statePop, excludedPop = 0., 0.\n",
    "\n",
    "for t in range(nTracts):\n",
    "    trueCountyTractList[countyNo[t]].append(t)\n",
    "    if t in allCutVTDs or t in skipList:  #  or vtdPop[t] < minTractPop:  #need to keep low-pop vtds as VEST may have assigned votes to them\n",
    "        excludedPop += tractPop[t]\n",
    "    else:\n",
    "        populatedTractList.append(t)\n",
    "        countyTractList[countyNo[t]].append(t)\n",
    "        countyPop[countyNo[t]] += tractPop[t]\n",
    "        statePop += tractPop[t]\n",
    "        #tractPop[t] = max(tractPop[t],0.000001)  #avoid possible later div/zero errors for nil-vote vtds\n",
    "print(\"Of the total statePop\",statePop+excludedPop,\"we ignore\",excludedPop,\"as it is cut out of the map\") #,\n",
    "#\"or in sparsely populated areas (<\",minTractPop,\") per geom\")\n",
    "print(\"This excluded pop comes from a total of\",nTracts -len(populatedTractList),\"tracts\")\n",
    "true_nDistricts = nDistricts\n",
    "nDistricts -= nCutDistricts\n",
    "print(\"Our final adjusted number of state districts, excluded fixed cut-out is\",nDistricts,\"rather than original\",true_nDistricts)\n",
    "aDP = statePop/float(nDistricts)\n",
    "print(\"Each district will be drawn to house\",r3(aDP),\"= 1/\",nDistricts,\"of non-cutout state pop\",statePop,\"vs original=\",trueStatePop)\n",
    "print(\"Here is a county-level modified map with each county's fraction of a district pop\")\n",
    "\n",
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "\n",
    "cutCountyList, uncutCountyList = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    if len(countyTractList[c]) == 0:  #no vtds added to county b/c all were in cut lists:\n",
    "        cutCountyList.append(c)\n",
    "    else:\n",
    "        uncutCountyList.append(c)\n",
    "        countyGeom[c] = tractGeom[countyTractList[c][0]]\n",
    "        for t in countyTractList[c]:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "uncutMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "print(\"here is the\",STATE,\"map excluding cut and unpop coastal tracts\")\n",
    "\n",
    "for c in uncutCountyList:\n",
    "    plotPoly(countyGeom[c])\n",
    "    FONTSIZE = 8 #11  #reduce for TX\n",
    "    if countyPop[c] / statePop < 0.02:\n",
    "        FONTSIZE = 5 #7 #reduce for TX\n",
    "        plotCenter(r3(countyPop[c]/aDP),countyGeom[c], FONTSIZE)\n",
    "    else:\n",
    "        plotCenter(round(countyPop[c]/aDP,2),countyGeom[c], FONTSIZE)\n",
    "plotPoly(trueMAP,0.1)\n",
    "for c in cutCountyList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(\"cut\",countyGeom[c],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "91bf5db4-45db-41ba-b790-64b3e46bdea4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing pops in NE coastal county 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing pops in NE coastal county 14\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing pops in NE coastal county 30\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cList = [4,14,30]\n",
    "for c in cList:\n",
    "    print(\"visualizing pops in NE coastal county\",c)\n",
    "    for t in countyTractList[c]: #making sure I separate counties 4 and 14 - is the pop concentrated?\n",
    "        plotPoly(tractGeom[t])\n",
    "        plotCenter(tractPop[t],tractGeom[t],8)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations.  Plot countyPop/aDP\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "Working on county  40 distances\n",
      "Working on county  60 distances\n",
      "the max LAT-scaled distance between counties is 5.00044\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 5.00044  0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "Working on county  40 neighbors\n",
      "Working on county  60 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#For corners and outcroppings, we fuse county clusters\n",
    "collapsedCountyList = list()  #VA has independent cities that we will reassign to parent counties\n",
    "print(\"Now finalize the map topology before any squish operations.  Plot countyPop/aDP\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    if c not in cutCountyList:\n",
    "        plotPoly(countyGeom[c],0.2)\n",
    "        plotCenter(r3(countyPop[c]/aDP), countyGeom[c], 7 )\n",
    "        for cc in range(c+1, nCounties):\n",
    "            dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "            if dist > maxD and cc not in cutCountyList:\n",
    "                maxD = dist\n",
    "                #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in uncutCountyList:\n",
    "        if cc > c and cc not in cutCountyList:  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in uncutCountyList:\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "398fbc6d-3b05-4c1f-87cb-72d11cdd98bc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f9b3df93-d821-44ca-b4f4-b65d13baaffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.25 of 736714\n",
      "checking if county 18 with pop 4558.0 and 1 or 2 neighbors is less pop than 184178\n",
      "checking if county 29 with pop 169151.0 and 1 or 2 neighbors is less pop than 184178\n"
     ]
    },
    {
     "data": {
      "image/png": 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gWRFRKjGgEFErUtLTjPVEkiQYiiwwFFnahJZIlReH1h7BW58fhvz5YVzQqwhlkyth6uXUumQiasKAQkQtJCkzA7VLSkqgKAqOHz/e5vjx48dRUVGR1seWJAnmPi4M7ONCP18EjeuOYcUXx+F/9QRGOG0YMrEHbKNKIRnltNZBRGfGf4FElHEmkwkTJkzAsmXLWo6pqoply5Zh8uTJGatDcZhQdGkfXHPbRHzl8qHwW2W8/sEevPvkp2hYshex+lDGaiGittiDohNHwxFs94Vg5qA90lqGzvAsWLAAN910EyZOnIjzzjsPixcvht/vx7x58zJTQCuSLME6ohgXjCjGpJoADq49jP/sroG89QguL/7/4Lr0q0DfKWfcq4iIUosBRQc+OOFBicmAS4uckPkCSFrL0J/g3LlzUVNTg/vuuw/Hjh3D2LFjsWTJknYDZzPNWGrDwCsHo+++faj60yGsNQuobz6IkVYDek78JjDyK4DBrGmNRPkgqVM8Dz30ECRJwl133dXm+OrVqzFt2jTY7Xa4XC5cdNFFCAaDyTxUzvLF4jDKEkY5bQwnlHfmz5+PAwcOIBwOY+3atZg0aZLWJZ0kCxgFcOGoqzHr8h+hztkH7338Ijb86VqIj34LqIkdmxENAoE6IB7Ttl6iHNPtHpR169bh6aefxujRo9scX716NWbPno2FCxfi8ccfh8FgwKZNmyDLHO5SE4kiEFfR13ry01dVKII+Fi4gRaQ7Qk18l2Vg0DSMGjQDo2p24finz+PfWz+Be/vHmGhWsbnRg0OWclzQsAGVw2chqJghK0ZYJnwHcFQA9uL2dy0EQlEVVpPScuyTPbUIhOMYUu5En2Jbpp4lkW51K6D4fD7ceOONeOaZZ/Dggw+2uezuu+/GD3/4wzYrQQ4dmv5VKfVMCIF/Vzegr9UMuyLj3dpGKJIEGUBdNIbrywu1LpGoBfvxmqhNg3GkVh+uSoegfM6vce2h9Yht+huW790Gg2xCZbgG/ym+ED0OHUCRoxgN3locOvw79A8egh9uBEbdi29cOgEAEFcFbn11A94/VI+LipzYFYkgCqAmHoMUigMCeGPuBIzrw9cFym/dCih33HEH5syZgxkzZrQJKNXV1Vi7di1uvPFGTJkyBXv27MGwYcPwq1/9ChdccEGH9xUOhxEOh1t+93g83SlJ19Y2+jGlwIEyc2IxqCF2i8YVEdFZqU09KB2deu01AYZeEzAzGkqMRzm4BheGGoGBlyZ+3/sRIst/jXBJT0T3vo+rNu3CyMGDMLKnCy9/ehBLjzZACsSwSvHj6j5FKLYY0afQhsvOqcD5f1qF7728ASUFFjRAxY1DyvGtSf1QZE/0tB5rDEGRJZQ6OQ6GcluXA8orr7yCDRs2YN26de0u27t3LwDgF7/4BX77299i7NixePHFFzF9+nRs3boVgwcPbnebRYsW4YEHHuhG6fpUFYrAIksoNSXCyP5gGDEhWsIJkZbCBz3wrz3Wshhb3BtBeHcDjBU2KEVWRI/5objy55Sj92//QvRQY4eXqcEIgOFn7lIyNn3Y6HvK1OgBF8M04GIc2PABBu96DUXuIK54ZR2sFgOCoRjcJgM+++klUIWAzdT2Zfh304binhW7Ue0NQm6M4OFQFIs3VuGWYT0Qiqn465fViAmBWT0Lce+0IRhU5uh+AxDpWJcCSlVVFe68804sXboUFkv7XgC16RPHD37wg5apguPGjcOyZcvw3HPPYdGiRe1us3DhQixYsKDld4/Hg969e3fpSehBTBVYUtuIflYTTghgizcxKLg6EsVXeAqHdCK4qQbBzTUwVjoAKRFQgMR3xW2GqZ8b1rFlGleZOZ7NDghRApP1YAeXGmBx7Idx4Ixu339p72EAgN/sewRrZ72J+kAUlQUWjOtTCItR6fA2N0zsjStG9YAiSTAbZGw90ogFr23Gb597Cv4P/gHVW4eK/kOx8uo7MO1IPeb2K8G88/tjRGViczZVFfjsQD0KbUYMLufKuJS9uhRQ1q9fj+rqaowfP77lWDwex4oVK/DEE09g586dAIARI0a0ud3w4cNx8GBHLwCA2WyG2Zz9XZVrG32YWuhAoZEzt0nHJAlKoRllt4/RuhJdkKQYnP12wvWD76Xl/gtKe2CZ82oMCW/Fd6f27/TtHOaTryOjexXge2VH8PGbT+PJJ/+AqVMmY/HixfjHn+/F1x95DX87Vo+//bMO/c1GjCl0YFWtB7XBKEyqwD/mTsDRhhDW7j+Bc/sW4bIR5acNRkR606V30+nTp2PLli1tjs2bNw/Dhg3DPffcgwEDBqCysrIlqDTbtWsXLr/88uSr1ZntviAOhxKfQIuMBhQY+A+fdE6WAFXrIvKL1Oq/3fXoo4/i1ltvxa3fuwUA8NRTT+Htt99Gn2NrcOeE6xCOqNjnC2GbN4DZlYUYWGzHorX7cM3f1wMAZIOMv+w+DumdrfjuyJ6YO6EXzql0J/fEiNKsSwHF6XRi5MiRbY7Z7XYUFxe3HP/JT36C+++/H2PGjMHYsWPxwgsvYMeOHfjnP/+Zuqo1ElUFPm30wRtToUjAMIcVl5XwHzllD0kGhJo7mwFmAwkCahIBJRKJYP369Vi4cGHLMVmWMWPGDKxZswb/bnW8tRsn9cW+Wj/MRhmVbiv21Pjw0/e+wF92HcNfvjyGC4ucmDagBBcMLsGwCle36yNKl5Sfj7jrrrsQCoVw9913o66uDmPGjMHSpUsxcODAVD9URn3W6EddNIZ+VjOmFJghcVE1ykaSdHL6LCGxrn96/y1LEBBJPEZtbS3i8Xi7FXbLy8uxY8eO097OalJaxqUAwMiebrwx73z4wzHc+9oWvH6kDh/XeGD8bD/W3ToVxY7sP9VOuSXpgPLhhx+2O3bvvfe2WQclm3licaxp8KHCbMRM9pZQlgv6PYg2BLHzp2+3HBOt/pv4UbT6rdXPooNgI0755XTZR7T9UWp3XGpzSctvIvGbLMmQoUCWEl9GOTHTSLm2GD3Obzvmrdm2378F42EZqqwCCgBFAhQJQlKhSgKQBdxqIYLhKqSz/0Bu3YY6YDcb8Pg3xuExVWDI4g8wzmWD28pZhqQ/HNF5Bh/XeaFIEqYXu6Cwx4RyQDUO4YRnNwrKKpqyQPPftdS03Id0MiJIreNC69/RsjZI820SF8iJ36XWt5cgmi+WpHbfE9+k5hIgSVIimEitHk+SIBRAlQBVkQBZIBTyw1llh//oidM+V3E8CptUglrbcYhoHCKiAioSQQeJwFMXOYa4pwrp3P0nEba6v5J2SUkJFEXB8ePH2xw/fvw4Kioqun2/siyht9OMqsYgnv9kP+ae2xtOC4MK6QcDyml82uBDL4sJ/W3s9qTcEVIC2B5egzt+8TetS0lK+IQfNQ9vQPioFzWb9kCV4oBRgtnlgKXABbPNBmEEGkUtxv78q6e9n6e+dTnGVPRMa62ylNwpHpPJhAkTJmDZsmW49tprASSWdFi2bBnmz5+fVG3/PaEv7vloF36x6QDe21+Lv3/7vKTujyiVGFBO40Q0hvMKuAAS5ZZoKAhjB2sYZRuD1QRVxOE+6ET44JGW41EAXiEQE1EUyiXwivqz31lHp65SKByNIRJP7jEWLFiAm266CRMnTsR5552HxYsXw+/3t6w31V0XDC5B5dr92BsKY3qf9nsGEWmJAeUUQgisavBhoC37X8SJThUJhWCyWLUuI2mKzQj7d/shWN0ASBJkIQMxgag/hKgviFggjmDIC9uAs5y8ycCZ21pvGG45ubndc+fORU1NDe677z4cO3YMY8eOxZIlS9oNnO2KjVUNuOX1TYipAh/cOIkr0pLuMKCc4q2aRkwucKDExKah3BOPRqAY9THO4Mknn8TDDz+MY8eOYcyYMXj88cdx3nmdP8VQPLwfMDy5GhLjQ9KbUgqsCpRo8ru5z58/P+lTOs1eXXcQ9676EoNtZjx/w3hUFmR/aKXck/y/mhxjkiWGE8pZsWhUFwHl1VdfxYIFC3D//fdjw4YNGDNmDGbNmoXq6moNqknvKR631QCrzl5TfrlmL9S6MB67ahTDCekWA0orEVVFYyyudRlEaROPRmEwaB9QHnnkEdx6662YN28eRowYgaeeego2mw3PPfdcxmtJRTx58skn0a9fP1gsFkyaNAmffvppqwdIbpBsOjwweSCMRWbMfHkdlmw92nI8Go9iW+02vH/gfbyw7QU89OlvURus1bBSymf6ivUaW3bCg+vKuLEfUTqdaWXU1atXa1BRcuGhuTfoqaeewqRJk7B48WLMmjULO3fuRFlZWdILtaXDVyf2xpVjKjHnz6tx+/tfYNyGKpQ79mBz7DVUSwWQVT+MshlhmFETegK/u+gXWpdMeYg9KE2EEDDKMoyyvl5IiFJJMRgRj8U0reFMK6MeO3Yso7VIZ1pcrpPO1hskZWC12u6wGBW8cfP5uGdsH8gAlnrWoy7mx4+HnIsVVz6KTdf/GUq8Bm8d+QIrD68EAASiAUTVKOIqe5op/diDAiCsqni31oMLCjmKnXKbYjBoHlB0RQKSSSid6Q2SIKDqdKFHu9mA2y4ZhNsAnP+X38Ae74kfjPl+y+X/O/p6PLljKW5e9RxsyvMIxIIAAFkyYIzLhfNLB+FrQ65HL2cvjZ4B5bK8Dyj7AmFs9gVwRUkBe08o58kGA9RYVNMa0rUyancku9NwZ/bJ0WsPyqmEUKGg7Y7s3xrxTdw4/Bt498C7OOw9jCJLEbwRLzbW7sThcBR//PJTPL17Bb6Y+0/uT0Ypl5cBRQiBzb4gqsNR9DAbcQ3HnVCekBUF8bi23fPpXBm1O9K+T44QOCe8Eav/cFvTrgFS0xYAiX0BRGKN/1a1NB1vuRyokrxYYTMgaO0JRVJgkA0wSAoUWYFRNkCRDTBKhsTvigFG2QCzYoDNZIHNaIHDZIXTbIHDZIPTbIPLbIXbYoPdZIFBTrwNqIhDlpR25UuShNn9Zrc59p2m72/ueRMLNryFB9f+BneOvx0uE3dFptTJy4DyenUDxjhtGFNi07oUoozSy4fcdK2M2i1JrCTbmd4gtc9UVH2xCz1rVzSdURJNsaQ5jpz8furPzbHl7RIJaw12xEJuAHEAKoSktvwMSYUkde95CKFAUk2AEoQi9+3Sba8ccCVqg/V4ZMeHePngHRjoKMFPx3wNU3pO6VYtRK3lXUCJqQJug4IB3GOHSDPpWBm1OzxhA/zB7o/J6Uxv0Lk3/A+A/0mqTvWvF2FCPIQ/37zytNeJxeMIx2OIxGIIxaLwR8PwhUPwhgOJ79Eg/JEg/JEQAtEgAtEQArEQgtEggvEQwrEgvjFyTpfqkiQJ80Z+B3MGzMaHVR/i/vUv4OYVv8Fn1/8VDhPH9FFy8i6gbPIGMM7FnhMiraVyZdRkbN11ArOSuH0meoM6M1HZoCgwKArspsx/+CqzleGGoTeg3FaB2z/5E65454d4efovOXiWkpJ3AaUxFkehMe+eNhGdxvCBRUndPhO9QUIISDofaFvlqcLmms0wIIgj8VJ8UPUBvj3i21qXRVks796pY2neuZRI9/hvoEWBMQhH7PjZr3gW6e4NyoZ5QP+96nfY5gtgWtkQXNV3Kqb1nqZ1SZTl8iqg1ESiKGLvCeU1vb/NacCX2cXhukMIoftpvBbZAKPw4aah38WUSg6SpeTl1UqygbgKp6H9NDoiylOKAeg5UesqcsITF92L8QWlmL/mOWyr3aZ1OZQD8iqgVJiNOBqOaF0GEemGBJEFp7z0XyFQYi3BExc9gFKjjOuW/xZ/3/lPrUuiLJdXAcUoSVCz4V86EWWEvk+anJSYxaP/agssBfjHrN+ij8GL5/dosfEj5ZK8CigSsuOTCFE68d9A9smGQbLN/BE/qlUXhjq4DgolJ69GjEqShMZYHJu9AQy1W2CWT+azE5EYjoYjGGa3wsA9eShXSRJn8ZwiW07x6PlV6ajvKH70ySMY7iqBJ1yLcDyEeybcrnVZlOXyKqAAwFfKC1EdjmJdox+RpvM9KoAio4JKswnvnWhEb4sJo5xczI1yj6woqD96GE/d9p2zX7mVbr05tp51IjVvy9f6WOuLWz9C4udzr74eY2de0Z1H7jw9v+u3ovdTPOuOr8On3ijW12+EgIyLSvuiwp7ZjR8p9+RdQAGAMrMRZWZjh5ddUVqAA8Ew/l1dj8uK3bApeXUWjHLc6GmzYDSbu3Sep3s9DKLptu2Ptb7gdJdv//gDHNm5Pf0B5ZSy9Ey/8QSY3W82dtXvw5/2+XF9ZT8smvozrUuiHJCXAeVs+lrNCKoq6qIx2BST1uUQpUxBRQ9Mvv4bWpdxVkd374CagV2XW+8hrGd6P8VjUkz48cQ70Ri6D28eP4BFWhdEOYHdA6chITFehYgyz2C2IBoJa12GbqgQUHQdURLO63EuAtEgdtfv1roUygEMKKcx1G5BKK5iuy+odSlEecdssyPs92tdhm6okCBlQU/PRb0ugoQ4ntj8otalUA5gQDmDCW47qiNR1EW7vx07EXWd0WxGNBzSugzdEBCQpMy9XD/55JPo168fLBYLJk2ahE8//bRTt9vbuBdCMuOCHqPTXCHlA45BOYuLC534V3UDrikrgKLzvTCIckUkKKF63x48cfNtUONhCFWFgASIpn+DkpSY1SIlvuJRFYAEo1kBICcmDUkSJMhIXE0CJBmyYoRiMEExmqAYTGgMm3H4iAGrH/0LhACEmhi42/wFCBRVOjDy2zdo1hYAIIk4VLnjgf2p9uqrr2LBggV46qmnMGnSJCxevBizZs3Czp07UVZWdtrbHfUdxYJVj6DUaMDVA6/OSK2U2xhQzkKSJFxR4sayEx4IJAKLhTN7iNLKaBsGg2Uf7IVOKEYzZEWBLKNppGgiPQhVhRACQgh460KIBKJwllgTs46ajrf5WVWhxqOIhn0IB6JQ4xFIsgNBdRC+3OsAJAEZApIkIEEFJKAuVAHD/hBGflvb9pBVAWHIzOvOI488gltvvRXz5s0DADz11FN4++238dxzz+Hee+9td/2YGsPjn/8Rf/zyUwAq/nrR7TAr5ozUSrmNAaUTLIqMmSVuRFWBFfVeTC92aV0SUU5zlvRDUe+v4NsParsr7qe/fwHbd2m/ImoUKmxy+l+uI5EI1q9fj4ULF7Yck2UZM2bMwOrV7ZeuD0QD+M6ye7DJG8B/DToP3z3nWyi0FKa9znT5MhDCwWAk6eHIddEYiozt/3/FhMAQuwV9rQxwncGA0gVGWc9LJRFRqsWiKgyy9rP5oiIOo5T+l+va2lrE43GUl5e3OV5eXo4dO3a0u/7ao2ux2ePF78+di8v7X572+tLJH4tjTyCMWSXutD7OF74g3q1thFNRcH6BHTKHDpwWz1V0USwLlsUmotRIBBTtB8lHhYAxAz0oXTW8eDiMEPj46EatS0mKEAJLT3hwWQZ6x4c7rJhV4sY5DgveP+HBu7WNqOdEjA7p7y9ex7b7gig1ZWagGhFpLxYFDIr2PSgxqDBmYJBsSUkJFEXB8ePH2xw/fvw4KiraL10vhEA87sHG+oNnvW9VqFh/fD2KrcUY4B6QsppTYUW9DxcUOjPam+E2GjCzxA1VCKxr9KMxFkdPiwnnOKwZq0HvGFA6aU2DD26DgnEu7tFDlO2efPJJPPzwwzh27BjGjBmDxx9/HOedd16768XiEo77e2LVw88mZgM1n+RtmiWU+FFqGrzbtF+6OLk2rRBApMaHyvr1KJBPQFJkQJYhyTKgtP6uNH2XAEVpup7SdLmC4UfjMFmr8a73F4mZSEYjZMUAg2JMzEhSjKgcNgG9Bo5Jql1MJhMmTJiAZcuW4dprrwUAqKqKZcuWYf78+W2u6414MX/FL6Aqbtw75syrE2+u2Yyff/o0vvB7IUkK7hp6AW4ffUtStabKl4EQCowKSkzavB3KkoRJBYlxTgeDYbxb2wizLGFKgQMmOb9PcjCgdMIGjx8mScJwJluijEjn59iuTKPtMdCN43UnsL/KkZjmDODkwvPN+wmd/Ln5eEteAeAN9YDneDVGHl8LoaJpBhKaJyMBatN+R62mOUPg5JRqAHMBAPUAXj3t89pVaUGv5Z93u12aLViwADfddBMmTpyI8847D4sXL4bf72+Z1dPs4XW/xcZQIUaYtuOiXhed9v6WH1yOO9a+iP42G56b+n28vfddPLJzLfZ7j+P/pv406XqTEYir2O0P4fLSAk3raNbHakYfqxnBuIqV9T5EVIExLit6mPNzyxUGlLP44IQHg+wW9Lbk5x8IUa7pyjTaUd++HqOSnGL8wi1/h3nQEAz89/Yu3U4IAcTjEKoKxGKJadWxGOLxKKLRMGLRCOKxCKLRMFb/+m4U7DuRXKFN5s6di5qaGtx33304duwYxo4diyVLlrQZOFsfqscrhw8ibhmJ3QEj3t77Nt488Al8cRXeWAw9zEaUm+2oClRjZZ0P00or8PjF/w+MshFTK6eiYN1v8OcDX+Jrxz7DxIqJKam7q4QQeK+2EVeVFWjy+GdiVWRMK3ZBCIFN3iA2e4MoMRow3mU7Zefv3MaAchYxIRhOiHJEV6fRpoaUOHXT1VtJEmAwJDpiTCdfgwwATp2karDYIIwNSdTY1vz589ud0mnNbXbj+l6Dsa9hGzYKgTs3/Ad20YAJxb3Rz2rF3oAPX/h8UEUcvx5zBa4bfC0UWWl5Xv819r/w7L7bse74Ok0CSiCu4t3aRlxa5NT1ApySJGFs07CCmkgU753wQJEkTC6ww64oGleXfgwoZyCEQEBVtS6DiFKkq9NoU0FASvunXhGNQjVk7g1LlmQsmpI4PbO3YS821WzC7P6zYTV07jT4z1b/FgZZwcW9Lk5nmR06FIpgkzeAq7NsdfBSkxGzmtbjWtPgQ0BVMcRmQX9b7q6pwoByGsGmhH1hoVPrUojyUq7M6BeQkO5tdKRILKMBpbUBBQMwoKDzs3L+uv0l/Kf6GP5n6IUYUTwijZW197kngJCqYo5Oxpx0h1GWcGFR4n1phz+311RhQOnAdl8QB4JhXJVlCZsoVwjRMkkmpbo6jTYVBKS0v3HIsTjiRv3P+PjbF6/igW0r8O0+g3DLqJsz9riqEHiv1oPBdjPG2XJnJuYwuxXD7FY0RmN4/4QHAHCe246CDlaxzUb6/4vOsPdqG2FTZFxeynBCpB2RltMirafRNmueRjt58uSUPx7QNOenG2NQukKKqxA6n5Lqi/jwf9uW4KuVvXDfpJ9AztDuzN5YHK9XN+DCQgcG2iwZecxMa15TZUaxCzv8Ibxb24gd/qDWZSUtN2JWCpWbjVzOnkhjIrE5cVp0dhptqohuDpLtElUA6X6MJP1p8zMIqALzx2Su52R/MIxd/hCuKyvIi9kvsiTh/KY1VfYFEmuq2GQZkwscMOj876MjDCincCoKfHEOjCXSkgDS9obSmWm0qZSRMSiqClXH3fqBaAB/3L8LxfED6OnomZHH/KzRDwCYmea9dfSqv82M/jYz/LE4Pqz3QhUCE1x2FGu0IF13ZE+lGXIgGMal3K2YSFNCiLSMQWl2tmm0qSWnfQyKpApA0e8pntuWzQeEEd8beWPaH8sfj+PDOi/OcVjRj7sGw25QMKNpTZXPPAGs9/jRy2LCiCxYeFS/f9EaKTYZcDQc0boMovymIj2jZDUgJAmSku5TPKpu28sX8WG1V4Y5+BluHpm+0zuHQxG8W9uIDY0BzCp2M5ycQpIknOu2o8RowO5ASOtyOoU9KKcoMhpwKBTN26WFifRAIL09KJkkIKP6cBhr/u81GKxGjLnlMhjtqR2sKakC1iN12LtjDUzOApidBbBY7DApJphkk6bjL97Z9w4kEcNjF/8mLQNjN3sDOBqOooc5sU4IdawmEsWaBj/Gu2wY77ZrXU6nMKCcYrM3gCuyeI48US5I1zRjLTjRiOp4CY7tS3zoKXh/IwZdc35KHyNuMaLPlx6Er52HMAAvgIgChExA0AwETUBD/2J844WVKX3csznsO4yfb/w3htjtmFyZ2llSQgj843g9LihwYLQzd6YOp5oqBD6s88KqyLpc1v9MGFBOEVFzZHUoomwmgPRuGZg53/zzNwEA1Z/twj/+fAiylPrXmKlP/wMHt3yCqM+DuM+HuN+HuN8P4fND9vuhfrYOQz9PzV49XeEyuaDIJlzfbzJsxtSGiD3BMM512VHJrUhOa5c/hN2BEC4pdMKu0UJ+yWBAOcW5bjvWNfpxbpZ0gRHlIiFE2me+ZFqsaWybkoZZFO7iHhh1yfWnvfw/v/geom9+kvLHPRunyYnBDhce2voOhhQOwdSeU1N23/uDEczghIYONQ8UHmgzZ/WquTn2EpC8nhYTPLG41mUQ5bcc7MiMBRMBxajB3ilqOISYQZuX+z9c+D+YVNwb81Y9h1uX/w/WH1+vSR354tMGH9Y0+DG7xI1hdv3P1DkTBpQOqLmyCQhRlkpMM86NUzzNYoEwAMCgxWqmoTBiJm1e7ns6euL5Gb/FQ2OvxH6/H9/66AmsPbo2qfsMxFVYsnDhsXQ6Go7greoG9LWaMb3YlRMrofMUTwcYT4i0JQQQ9Eaw8f2DAE5ZtE1qPYBWajOYVpIlDBhbCpure+MSjhw6jjdffws9SvvAZDRBavVgEqS2s4skCVLT8eafm//z77f/P/z9Xy+hrr4OA/sPwg9v+zEqhBNhs8CedQdwbN8mQJIhyU07HTffHidH3vQYORKFgwZ163kAwJNPPomHH34Yx44dQ1+3FXf2KkXm9w5OkCUZXxlyHa4adCXO+9f38PCGZ/C3y8fDKBu7dX8bPH5McPE0PJD4QL28zgu3QcGVWTYI9mwkIfTVXeDxeOB2u9HY2AiXS5vzix/WeTDKYcuqFfeIcsmm5VVY+8ZeQLT6wCBO/iJa/pOYktz8sxoXOP/aAZgwu1+3Hvfpx5/H0RP7u103AGzduhWvv/465syZg169emHNmjXYvn075s+fD7u982+qPYJB/OD//q9bNbz66qv4zne+g6eeegqTJk3CgutnY/Wuw/h/xw6Gw25ExKwgalbQ4/b5mDgnPUv8n877B5Zh/rpXMcDQgK8Omo3+rv4YVzYOBZaCzt/HCQ/HnwA4GAxjkzeIacVO2BXtB8Gm+v2b78CtqELggzovXAaF4YRIQ2Om9caYab27fLu/3LMSarz7n7kK7MU4WnsA9957b6LHRAgICIimcHQyLCVOQzV/JQ4JQAWmX3Yp5n33Zvzm/x6GUAVUNY5RY0fBYrZi/i0/gIwYoKoQqgoIAaGech8CeOuZPyGcxOZ/jzzyCG699daW/YUe/9v/i8kXXYHXnTbMHTsYciiMXqt24sSKD4EMB5QZfafjF6E6PLtnDRbvXIlQbBlkSUaxuRAGWcYAmw3DncXo5+6Nfq5+6OvqizJbWUsvWus2z1eiqdek0Khk3dThruC7cJM9gRB2+LN3OhYRJU6PJPXeJUmQoMDSzVVII5EINm7aiP/9+f+isPjkomEzZ16GzVs2oaR3j07dj8FgRFR0b0+wSCSC9evXY+HChS3HBo+9GHOu+ypONDRg1uJXAQArzxsBaLR/z9eHfg1fH/o1CCFw1H8Ua4+uxY663YiJOHb7GvHmsQOo3b8RqkhMWDApZlRYCzHIZkOpoy+uGXglgPxclO14OIrVDT5MK3bBlePvVQwoSHST1UZiWT0di4iQGC+SREKRklx7pba2FvF4vN3Gg+Xl5dixY0en70cVarcHOXa2BiUOzQJKM0mSUOmoxHWDr2t3WVSN4rD3MA54DuCA5wC+bDyETY3Hsbz6A0wsKseEoqs1qFhbJyIxbPQGcG15odalZERSw7ofeughSJKEu+66q+XYJZdcAkmS2nzddtttydaZVkfCUQzSYmQ9EaVUkvkkMQBWB2cP4kKkfYNBY1xAGLs3SDUTjLIR/dz9cHHvi/Gdc76DX075Kb498EJYwtswpXKK1uVlnD8ex8oGL2bm0dibbsfndevW4emnn8bo0aPbXXbrrbfil7/8ZcvvNpu+lyGe5Lbjg6ZR0BO4QBtR9pKAQGMYNVXesweNpgk6LTOEJCDojSKZhFJSUgJFUXD8+PE2x48fP46KiopO348qBIzdXKmuszUYYoCkcQ9KVwgh8K/d/8K55eeixFqidTkZFVUFltQ04rrywpybfn8m3frr9Pl8uPHGG/HMM8/gwQcfbHe5zWbr0j9GrUmShGnFLhwKRfBRnRcXFzm1LomIusFkMWD7qqPYvupot24fsDUCzu6/AZhMJkyYMAHLli3DtddeCwBQVRXLli3D/PnzO30/qgDkbq7z0dkaDHHA/K9l+OLZ4QCA/SOKIBQZQpEBgwJhUABZBgwGwKAARiNGfO9uDBh1QbfqStZbe9/C5trNeHbms5o8vlZUIfBGdT2uKitIe6+a3nQroNxxxx2YM2cOZsyY0WFAeemll/DXv/4VFRUVuOqqq/Dzn/9c970oANDTbMR2X1DrMoiom665axx89R1vJd96FkjiO5pm5pycnrNxq8DnW48kVcOCBQtw0003YeLEiTjvvPOwePFi+P3+lhk1nRGHgJLELJ7O1FD1jQsQ338QJZ8k1poRJgOkmAopEoUUCEOKq5DiKuS4gKSqqDgSws6iF9IeUPY37scL21/AD0b/ABX2xAddf9SPR9c/isv6XobzepyX1sfXEyEE3qxpwOwSN0xJ/D1kqy4HlFdeeQUbNmzAunXrOrz8m9/8Jvr27YvKykps3rwZ99xzD3bu3InXXnutw+uHw2GEw+GW3z0eT1dLSpndgTCGpngbdCLKHJvL1O1F2gDAedQCKckVSufOnYuamhrcd999OHbsGMaOHYslS5a0G7R6JokelO6/IXWmhsvve6bNbYaf5T43jRwOsXwl3v5yOgDAGIhCGGSow0+/mJx7+ChMmXtnp+tuDDdi/vL5OOA5gOUHl+O3F/8W51aci2c2PwNPxIMfT/xxp+8rFyw94cEFBfk7s7RLAaWqqgp33nknli5dCoul4zfy73//+y0/jxo1Cj169MD06dOxZ88eDBw4sN31Fy1ahAceeKCLZaeHQZLAzYyJ8lsq1tiYP39+l07pnEoFoMjJvSklW8Opqi4cDMOhaqDBDwDoubsRMgDv7mqIDjKdOSzgs68GOhlQomoUP/7ox2gIN+CvV/wVv9/we9z63q24eeTNeHH7i/jeqO+h0lGZsuejdyvqvBjhsOb1mlxdeubr169HdXU1xo8f33IsHo9jxYoVeOKJJxAOh6GcsprdpEmTAABffvllhwFl4cKFWLBgQcvvHo8HvXt3fYGmVCg0KtjkDaC/Bpt5EZH2JEnSxSJgqoSkTvGkw5V/fKNL13/3v78KZcuuTl1XCIGH1j6Ez459hqcvexpjSsfg6cuexuL1i/HMlmdQYa/AvJGZXVBOS+sa/ehhNqKXpfu9gbmgSwFl+vTp2LJlS5tj8+bNw7Bhw3DPPfe0CycAsHHjRgBAjx4dL1BkNpthNusjEBQaDXAqCg6FInn/h0GUj2RZRjwex65du9otl9D6C8AZLy8uLoYxiSm8KgBZ0VdA6SqDP4ygtXO9QC998RL+vuvveGDKAy1jTAyyAT8+98eYUjkFRdYiWA3ZvTNvZ231BmCRJQzmcIOuBRSn04mRI0e2OWa321FcXIyRI0diz549ePnll3HFFVeguLgYmzdvxt13342LLrqow+nIejTeZcPyOi8DClEecjgciMfjePnll5O6n/Hjx+Pqq7u/kJgqSVCUbO/aFxCdmHWy4tAKPPzZw5h3zjx8ZfBX2l0+pWf+rHnyZSCEQFzFeQUOrUvRhZT+CzCZTHj//fdbRoz37t0b119/Pf73f/83lQ+TVjGRGItCRPln5MiR6N+/P1RVbbPXztm+gJN7xLz11lttBv53Ry70oHTmTNnOup34yUc/wSW9LsFdE+5Ke016djgUweFQlMtctJJ0QPnwww9bfu7duzc++uijZO9SU580+DDamR9diUTUXld2HO6IyWRKejGtRA9Kds/cEBBn3DigNliL+cvno6+rLxZduAhyNxemywV10Ri2eIOYXZqf+wudTv7+RXTg0wYfys0GFGbR6opEpC9CiKQDipDlnFiU63R7G4ViIfxw+Q+hqioen/Y4bEb9r5OVLv54HCvqvJhVkj9L2HcW34lbsSoyrDobOU9E+UeVJChZ3qMgTrNlgCpU/Gzlz/Blw5d4fvbzKLd3fn2YXKOK/FzCvrMYUFoZ6bDi3VoP+nZzq3UiIiEEjh49isOHD0OWZUiS1PK99c8dXQYkZgdFTSZI0SjUQACQZUiyDCiJpeez5Y3sdKd4ntz4JJYeWIpHL3kUI4pHZLwuPVnT4MeMYldO9JalAwNKK55YHCV5vCgOESXPbDbj4MGDeOaZZ85+5TMIvb8UO//0p/YXNIWV5tAitfoZigxJVgBVhfvaa1H2owXtb59Rbd9439zzJv60+U+4e8LdmN53ukY16Yc3HoebQwpOiy3TittoQH3Ur3UZRJTFvvrVr6KhoaFlJlBnvwMnZwKphw6h97nnQhIA1DhEXG36HgdUNfE9rkKocSB+yuVxFbV/+AOCmzdr2g4CbePJhuMbcP8n9+O6Qddh3jn5s+ja6ez0hzDYxrVOzoQBpZVPG3wY68rfwVpElDyz2dylfXc6dM45Sd08tG1bokdFQ63HoFR5qnDnB3dibNlY/Pz8n2fNaap02h8MY1YJZ+2cSXaPwkqx+lgcpabur/5IRKQHaiAAWQc7yEuQ4Il4cMfyO+A2u/HoJY/CqPA1ti4aQ0GebgDYFexBaeKNxfkHQ0Q5QQ8BJXHaSuBHH/4IJ4In8NIVL8FtZo8BkNhrZ2YxpxWfDXtQAMRUgaUnPJjgSm6BJiIiPdBFQJGAQNSPz459hkcveRT93P00rUcvoqqA0mrWFp0eAwqAD+u9uKLEDYPMPxgiyn6SwQARjWpaQ/PA3/sm39eyASAlViufwr12OoWneJBYLMeS5fteEBE1M5SWIFZbq2kNPR09EXNKOHfwdZrWoTfBuAob3286ha0EoJ/VjLdrGlAXjWldChFR0gylpYjV1GhaQ7m9DKW2Uk1r0JtN3gBGca+3TmNAATDEbsHlJW7s9oewpKYRXwZCWpdERNRthrIyxI4f17gKCadZ7T5vHQ1F0dNi0rqMrMGA0kSWJEwqcGB2qRsyJPy7uh61EfaoEFH2MZRXIFZdDaGqWpdCTY6EIuhh4RTrrmBA6cAAmxnXlBVihz+IT+p9WpdDRNQlhpISiGgUqsejdSnUZLM3iDFO7demySYcJHsGFxQ6UR2O4t/V9ZhTUsBZPkSUFRSXEwCw97qvoPye/4EIh6GGwxCRKBCPQcTiELEYRDwGnO7neBwiGmtaPj/W8rOIx4BoDEKokBQDJEVp2RPo5HcZwc83wlBWpnFL6EMgrsKi8P2jqxhQzqLMbMTsEjfeqGnA9CInN3YiIt2zjh8P84jhCG//AofvurvluGQyQTIYAENTsDAokAzGxIaDigIYDSdDh8EAqaPrGY2QLFZAlhL7AcUT+wGp0WjTvkCJ3w0lJXBOm6ZhK+jHJw0+XFzo1LqMrMN3204wyzKuKyvAqgYffDEV41w2lJt5LpGI9Em2WDDgtdcQq6tLBAqzOfGdi4NlnBACcSFgZA98lzGgdJIkSbigKQF/WOeBAFDBkEJEOmYoKtK6hLy3wRPAeG5C2y0cJNsNE1127A+GtS6DiIh0rjYa4ya03cSA0g0xIVATieGDEx6E4mrLks5ERETNDoUiqGRPe7fxFE83FBgNuKqsABFVxZJaD6KqigsLnSjjHyIRETXZ5gtiVgl3cO4u9qAkwSTLuLqsANdXFGFNox/BOBdFIiKixJ47Zg6MTQp7UFJkoM2MD+s8iW20gZbR8gUGBWOcNo7gJiLKI580+HBhIXctTgYDSoqc47DiHEf7TaAaojF8WOdBXACKhJYAA5zcpiImBKYWOGA3KBmrl4iI0kMIgZgQMMk8SZEMBpQ0KzAacNlZzkGqQuD16gZcWermHzQRUZb73BPAOC5rnzS+G+qALEm4osSND+u8WpdCRERJqonGOGkiBRhQdMKiyJC5yiMRUVY7HIqgB8NJSjCg6IhLkVETiWpdBhERddP+YBg2hW+tqcBW1JFz3XasbvCjLhrTuhQiIuoGf1zFAKtZ6zJyAgOKjkiShKtK3djsDWBlvRcqV6glIsoacSEgATxdnyIMKDojSRIuKXJhlMOKf1c3sDeFiChLrGnw4fwCrn2SKpxmrFNuowHXlhVgVYMPIVXAIAH9rWb0sZi4ZToRkQ754yqcXM8qZRhQdEySJFxQ6ASQWCtlXzCMD+q8LQu8SQCmFDhg4YAsIiJN7fKHMNhm0bqMnMKAkiVkScJAmwUDW/0DiKoCqxq8iKoCToOCUU4r7ArTOxFRpu0PhjGTGwOmFANKFjPKifEqQGJJ/S3eIGojMQyxWzDEziRPRJQJDdEY3Dy1k3IMKDmiwGhoGZz1hS+I92obYZVlTC5wwMCNComI0ubTRj9mFLu0LiPnMKDkoOEOK4Y7rAjEVXxYn1g+v8RowFgX94YgIkolTi1OH46uzGE2RcaMYhdmFLtQYFTwYZ1H65KIiHLK6gYfJnNqcVowoOSJflYzBtsseKu6AcfDXE6fiCgVAnEVDo4/SQsGlDzS02LClWUFWNfoh+AqtURESdnhD3JCQhoxoOShMS4bNvuCWpdBRJTVDgYj6Md9d9KGASUPbfQEMMph1boMIqKsVc+pxWnHgJKHBtrM+E9tIxq4zw8RUbesa/TjPLdd6zJyGgNKHhrhsOKKEjfWNPi1LoWIKOs0Ty3mvmjpxYCSpyRJgiIBobiqdSlERFmFU4szgwElz5m5yiwRUZdwanFmMKDksUqLCV8GwlqXQUSUNXZy1+KMYUDJY+c4rNjDgEJE1Gn7g2H0t3FqcSYwoOS5wXYz/lPTAF8srnUpRES6VheNoYCndjKGmwXmuYE2C/pbzfi43oeQquLSIidMMnMrEdGpPmv04zLuWpwxfCciyJKEi4ucmFbkwpvVDYionNlDRNRabSTGqcUZxoBCLYyyhCvLCrCq3oeltY3Y4edy+EREAPD4geOYwqnFGcVTPNSGWZZxaVMX5t5AGO/UNMCpKBhoM6PSYtK4OiKizIupAhcVOWHn+JOMYkCh0xpgM2OAzYyIquLLQBhrjtfjurICdnESUV5Z5/FjEpe1zzie4qGzMskyRjisON9txxbugkxEecbPhdk0wYBCndbDbIQvpuK92kZs9AS0LoeIiHIYAwp1miRJmFLowMwSN0yyhC/Ym0JEOc4Ti8Ol8K1SC2x16pYRDitORGNYWe9FXAityyEiSotNngBGO21al5GXkgooDz30ECRJwl133dXuMiEELr/8ckiShNdffz2ZhyGduqDQidFOG5af8ODDOg8EgwoR5ZiIELCwB0UT3W71devW4emnn8bo0aM7vHzx4sWc7ZEHXAYFl5W4MdZpw5s1jVAZUogoh/AVTTvdmmbs8/lw44034plnnsGDDz7Y7vKNGzfid7/7HT777DP06NEj6SJJ/wqMBkwrcmJ5nRfNsVRq+ioxGTDSYWVgJaKs4o/HYZX5uqWVbgWUO+64A3PmzMGMGTPaBZRAIIBvfvObePLJJ1FRUXHW+wqHwwiHT+6o6/F4ulMS6YDDoGDGKftUqEKgOhLD0hMeyE0BpY/FhME2MwMLEenaZm8QYzn+RDNdDiivvPIKNmzYgHXr1nV4+d13340pU6bgmmuu6dT9LVq0CA888EBXy6AsIUsSKsxGVJjdLccOBMN4o6YBUwocKDUZNayOiOj0qiNR2A1c3l4rXRqDUlVVhTvvvBMvvfQSLBZLu8vfeOMNLF++HIsXL+70fS5cuBCNjY0tX1VVVV0pibJQX6sZV5cWYEWdlxsTEpEuCSHgULg4m5Yk0YWpF6+//jquu+46KK3+p8XjcUiSBFmWcfvtt+PJJ5+ELMttLpdlGRdeeCE+/PDDsz6Gx+OB2+1GY2MjXC5ua53LoqrAmzUNuKTIiSIjd10gIv34MhCCQZLQz2rWupSsker37y4FFK/XiwMHDrQ5Nm/ePAwbNgz33HMPSkpKUFtb2+byUaNG4bHHHsNVV12F/v37n/UxGFDyixACH9V7UWI0YCTP9RKRTiw74cG0IifHynVBqt+/u/Sx1el0YuTIkW2O2e12FBcXtxzvaGBsnz59OhVOKP9IkoRLilzY7gtiQ6Mf47khFxHpgAAYTjTG1WdIF0Y4rKiOxBDmmBQiIkI3pxm3drZxJVxdlDprRrELr1fX47ryQij85EJEGjkSiqCHmTMMtcYeFNINgyzh8lI33qxuwJFQROtyiChP7fCHMMzefqYqZRYDCumKXVFwbXkhNngCXDafiDQhAPbi6gADCunSpAI7Pq73aV0GEeUhfjTSBwYU0qVSkxF9LCZ8cIJbHxBR5tRFYyg0cIE2PWBAId3qbzNjqN2CT9iTQkQZssUbxCinVesyCAwopHOVFhOCnHpMRBkSFQImmW+NesD/C6R7NkVGQzSmdRlERJRBDCike5Pcdqxq4GkeIkovfzwOq8zZO3rBgEK6J0sSRtitWM2QQkRptMkTxFjuCaYbDCiUFfrbzPDG4lqXQUQ5LKCqsHMGj24woFBWOB6OoszEpaeJKH24NYu+MKBQVtjhD+EcB6f+EVF6RFUBI8ef6AoDCmUFXzzOFw8iSpsDoTD6W81al0GtMKCQ7h0PR7mzKBGl1aFQBL0sJq3LoFYYUEj3DoUi/GRDRGmlCm4QqDcMKKR79bE4Co0GrcsgIqIMYkAh3eNnGiJKN87f0R8GFNK9UpMBewIhrcsgohzGD0L6w4BCujfaacPeQFjrMoiIKIMYUEj3qsNRVHAWDxGlSUwVHCCrQwwopHs2Rca+YISrPBJRWjTE4igwcol7vWFAId1zGBRcXOjAv6obEFZVrcshohzTEIuhgHvw6A4DCmUFt9GAq0sLsPyER+tSiCjHNES5lIEeMaBQ1lAkLqRERKnnjcXhVPh2qDf8P0JZY2W9D+e57VqXQUQ5RgCQ+OFHdxhQKGvYFRlhlQNliYjyAQMKZY1xLhtW1nvhjcW1LoWIiNKMAYWyhiRJ+Ep5IT6u92pdChERpRkDCmUVSZJglvlnS0SU6/hKT1knzgXbiIhyHgMKZZX1jX70t5q1LoOIiNKMAYWyyuFwFINsDChERLmOAYWyygWFDiypbdS6DCIiSjMGFMoqRUYDxrvsWMmZPESUAlFVwMBF2nSJAYWyTrnZyAXbiCglGmIx7mSsUwwolJUYT4goFRqice5krFMMKJR1/PE4VE41JqIUaIjFUcCdjHWJAYWyzsp6Hy4tcmldBhHlAKdB5vYZOsWAQlnnggIH3q5pwMp6LyKqqnU5RJTF+lrM2B8Ma10GdYD9WpR17AYF15YXIhhX8UmDD1FVoMJsxCinTevSiCjLWLlLum4xoFDWsioyLmk61XM4FMF/ahpQaTFhDIMKEVHW4ykeygk9LSZcXlqAAoOCD054tC6HiIiSxIBCOaWv1Yw+VhPWNfq1LoWIiJLAgEI5Z6DNAgA4yIFvRNRJgksX6A4DCuWkc912LKvzwsfpg0R0FuVmI6ojMa3LoFMwoFDOuqGiEBs8Aa3LICKd62cxYR97XHWHAYVyUmM0hvdqPZhc4NC6FCLSObtBQSDONZX0htOMKefsD4axyx/CtWUFkLhLKRFRVmJAoZyyusEHBcDMErfWpRARURIYUChnrKz3YpDNggqzUetSiCjLsK9VfzgGhXKCLxZHMK4ynBBRtwhwqrHeMKBQTvikwYfpxdzhmIi6p8hoQF2UyxLoCQMKZb29gTAKDApkDoglom7qZzVxV2OdYUChrPZ2TQMaY3Gcx+nERJSEAqMBjVzYUVcYUChrxVQBh6JgnIu7FxMR5RoGFMpaBlmCykFtREQ5iQGFshrjCRFRbmJAoazFKYFERLmLAYWyVkQIGDlzh4hSxG1Q0BDlrsZ6kVRAeeihhyBJEu66666WYz/4wQ8wcOBAWK1WlJaW4pprrsGOHTuSrZOoHbMsI8peFCJKkX5WM/YHI1qXQU26HVDWrVuHp59+GqNHj25zfMKECfjLX/6CL774Au+++y6EEJg5cybicU7fIiIi/SoyKqhjD4pudCug+Hw+3HjjjXjmmWdQWFjY5rLvf//7uOiii9CvXz+MHz8eDz74IKqqqrB///5U1EvUhgpwJg8RpQR3P9eXbgWUO+64A3PmzMGMGTPOeD2/34+//OUv6N+/P3r37t3hdcLhMDweT5svos4a57RhgyegdRlERJRiXQ4or7zyCjZs2IBFixad9jp/+MMf4HA44HA48J///AdLly6FyWTq8LqLFi2C2+1u+TpdkCHqSLHJgAau/khElHO6FFCqqqpw55134qWXXoLFYjnt9W688UZ8/vnn+OijjzBkyBDccMMNCIVCHV534cKFaGxsbPmqqqrq2jOgvBcXglOOiYhyjCS68Mr++uuv47rrroOiKC3H4vE4JEmCLMsIh8NtLgOASCSCwsJC/PnPf8Y3vvGNsz6Gx+OB2+1GY2MjXC7uTktnVxeNYac/hMncj4eIkrS2wYdzHFY4DMrZr0xtpPr929CVK0+fPh1btmxpc2zevHkYNmwY7rnnnnbhBEgspiWEQDjMXSIpPSyyDHagEFEq9LeasT8Yxkgn9/jSWpcCitPpxMiRI9scs9vtKC4uxsiRI7F37168+uqrmDlzJkpLS3Ho0CE89NBDsFqtuOKKK1JaOFEzsywhrKpal0FEOaDUZMBWX1DrMggpXknWYrHg448/xhVXXIFBgwZh7ty5cDqd+OSTT1BWVpbKhyJqoXBqIBGlCKca60eXelA68uGHH7b8XFlZiXfeeSfZuyTqsoZYHHsDYQywmbUuhYiIUoB78VBOuK68EHEh8Prxevg47ZiIKOsxoFDOGGy34JqyAnxc79W6FCIiShIDCuUUSZJg4DlkIkqCRZYRiHPgvdYYUCjnGCTO6iGi7utnNeFAkEtjaI0BhXKOJAF7A3xxIaLuqTAbcSwc1bqMvMeAQjnn4kIn9vPTDxF1kyxJ4NqP2mNAoZwjSRJ6Wkyo5icgIqKsxYBCOekchxXbuBokEVHWYkChnKRIEjhMlogoezGgUM4ySBKqQhGtyyCiLGTiHl+aY0ChnFVmMnAkPhF1Sx+LCQeD/ICjJQYUylnDHVYoEvBWdQMOsSeFiLqgp8WEw2G+bmiJAYVy2niXHVeWFWCnP4SltY3YEwhpXRIRZQFFkqByrrGmGFAoL0wvduGyEje8MRUbPQGtyyHKWytWrMBVV12FyspKSJKE119/XeuSSKcYUCivjHXZ4DDIWFLTiNUNPtRGYhynQpRBfr8fY8aMwZNPPql1KaRzBq0LIMq0QTYLBtks8MTi2BsIQ5GAzd4ADJIEuyLjHIcVDoOidZlEKdPYuBGHD78EQAIkGRKaNtRs2VhTavpvq402T7ms3XUkAJAhSTIkyIAkNX1vuv/m46fc59BhwNBh5QAOAQCOH38b+/ZVtbte23pkSJIESAqkpsdM3L+SeNym44kalFaXy5AkpcPjgJT4HejwmCTJ8AdkxAuGQVEs3Wh1ShYDCuUtl0HBWJcNADDKmTjmi8WxzReEr9VOpoVGBSPsVlgUdjhSdqqufgdHj70Gt3s8hBAAVEAkBliIlkXdWw+4EKd86+A6Qm06LiCECkBtue+T3+PtixFtB3acOLEChw5vaffYQohTfo833afa9HhxCCFajqfDXozG7tAUDBv8k7TcP50ZAwpRKw6DgkkFjjbHTkRi+MzjR1g9+TJdZFQw0mGFSWZooexgsw3ExAn/0LqMU0gYMeL/cOEF1yZ9T4ngcmqIUTs4HsfJ0KOidcA69Zj/i8ewz3sMw5KujrqDAYXoLIpNBlxgcrY5VhuJ4eN6H4qMBoxr6oUh0rfcnpIiSfLJUzYpMsBVjlW1x1J6n9R5DChE3VBiMmB6sQtLaxsRiqs8/UOaCoWO4vDhlyFErOW0C4Ro+bmh/lOtS8xKLltvBCLbIYSa8vBDZ8eAQpSEi4uc+KTBh0uKXFqXQnmsumYJ9h/4A6zWPmgZUNoy6FMCIKG4+BJNa8xGNmtfQEQRDh+HxdJD63LyDgMKURJMsoxAPDEoUJKks9+AKB2ECkVxYMrkD7Su5Kx8Ph++/PLLlt/37duHjRs3oqioCH369NGwsvYSgQ8IBg8yoGiAfVZESZpa4MDr1Q2IcGMx0ojIovEln332GcaNG4dx48YBABYsWIBx48bhvvvu07iy9iyW3hCQEAwe1LqUvMQeFKIkuY0GXFlagA/qPJhZ4ta6HCJdu+SSS1pNIdY3RTHDaCxEIHBA61LyEntQiFLAKEsoMhqwLxDWuhTKS9nxhp+Nyi12HPLXaF1GXmJAIUqRiW47dnMzQtIIx0ClxwCbA/uD3L9LCwwoRCkW4xaolGlCoM1S8ZQyJfZKNIYbtC4jL3EMClEKuQwKPq73tulwl3CyA775LeTU37ujs29JHV3vTLfV8q1OAJAlQIGU+C5JUKTELimyJEFpOiaj+bJTf08ck1vdvvm2zdeRpaYJuKfpcdjiDWCUM7sW31MFEItHcPDg84AkmgKLgGha0l40rYuS2JMGJ/eeOXXfnHa/S0374TQvgia13c+mzf47MhoaP4PJWAybrf8pFZ6yrP4py9h3dIqqw4G/HWb/Tt721GMdjoNpfywcroYaDyAabYTRyDFmmcSAQpRC55+yTD51nSoE4gKIC4E4BETLz4nvaqvfm68bFQJxqC2XqU3XFaf+DiAuErc7VfMRTyyO2kiszTFA3/0TNfHBOIpR2LJnSUuQANC06V7iq3njvURriJY36Jal3VsWeGu6nFrYpBhUwV3PM40BhYh0RW7q5TDqOhLoTPGlwMBLU3qXJzf8O3UjwLb714jmTQOFinCkGrJshtHQvHDhKTsit+xSjFbHm4512KPV/WOdH5Nz9vuTZQNk2dzJ+6NUYUAhIqJ2Em/wCiRJ6fRtzOay9BVEeYeDZImIiEh3GFCIiIhIdxhQiIiISHcYUIiIiEh3GFCIiIhIdxhQiIiISHcYUIiIiEh3GFCIiIhIdxhQiIiISHcYUIiIiEh3GFCIiIhIdxhQiIiISHcYUIiIiEh3dLebcWJLb8Dj8WhcCREREXVW8/t28/t4snQXULxeLwCgd+/eGldCREREXeX1euF2u5O+H0mkKuqkiKqqOHLkCJxOJyRJ6tJtPR4PevfujaqqKrhcrjRVmD3YHm2xPdpie7TF9miL7dEW26OtjtpDCAGv14vKykrIcvIjSHTXgyLLMnr16pXUfbhcLv4BtcL2aIvt0Rbboy22R1tsj7bYHm2d2h6p6DlpxkGyREREpDsMKERERKQ7ORVQzGYz7r//fpjNZq1L0QW2R1tsj7bYHm2xPdpie7TF9mgrE+2hu0GyRERERDnVg0JERES5gQGFiIiIdIcBhYiIiHSHAYWIiIh0J2cCyoYNG3DZZZehoKAAxcXF+P73vw+fz9dy+YkTJzB79mxUVlbCbDajd+/emD9/fs7u+XO29ti0aRO+8Y1voHfv3rBarRg+fDgee+wxDStOr7O1BwD88Ic/xIQJE2A2mzF27FhtCs2QzrTHwYMHMWfOHNhsNpSVleEnP/kJYrGYRhWn165du3DNNdegpKQELpcLF1xwAT744IM211m2bBmmTJkCp9OJiooK3HPPPXndHuvWrcP06dNRUFCAwsJCzJo1C5s2bdKo4vQ6W3s8//zzkCSpw6/q6moNK0+Pzvx9AIl2GT16NCwWC8rKynDHHXd06XFyIqAcOXIEM2bMwKBBg7B27VosWbIE27Ztw3e/+92W68iyjGuuuQZvvPEGdu3aheeffx7vv/8+brvtNu0KT5POtMf69etRVlaGv/71r9i2bRt+9rOfYeHChXjiiSe0KzxNOtMezW6++WbMnTs380VmUGfaIx6PY86cOYhEIvjkk0/wwgsv4Pnnn8d9992nXeFpdOWVVyIWi2H58uVYv349xowZgyuvvBLHjh0DkAj0V1xxBWbPno3PP/8cr776Kt544w3ce++9GleeHmdrD5/Ph9mzZ6NPnz5Yu3YtVq5cCafTiVmzZiEajWpcfeqdrT3mzp2Lo0ePtvmaNWsWLr74YpSVlWlcfeqdrT0A4JFHHsHPfvYz3Hvvvdi2bRvef/99zJo1q2sPJHLA008/LcrKykQ8Hm85tnnzZgFA7N69+7S3e+yxx0SvXr0yUWJGdbc9/uu//ktceumlmSgxo7raHvfff78YM2ZMBivMrM60xzvvvCNkWRbHjh1ruc4f//hH4XK5RDgcznjN6VRTUyMAiBUrVrQc83g8AoBYunSpEEKIhQsXiokTJ7a53RtvvCEsFovweDwZrTfdOtMe69atEwDEwYMHW67TmdeYbNSZ9jhVdXW1MBqN4sUXX8xUmRnTmfaoq6sTVqtVvP/++0k9Vk70oITDYZhMpjabE1mtVgDAypUrO7zNkSNH8Nprr+Hiiy/OSI2Z1J32AIDGxkYUFRWlvb5M62575KrOtMfq1asxatQolJeXt1xn1qxZ8Hg82LZtW2YLTrPi4mIMHToUL774Ivx+P2KxGJ5++mmUlZVhwoQJABJtZrFY2tzOarUiFAph/fr1WpSdNp1pj6FDh6K4uBjPPvssIpEIgsEgnn32WQwfPhz9+vXT9gmkWGfa41QvvvgibDYbvvrVr2a42vTrTHssXboUqqri8OHDGD58OHr16oUbbrgBVVVVXXuwpOKNTmzdulUYDAbxm9/8RoTDYVFXVyeuv/56AUD8+te/bnPdr3/968JqtQoA4qqrrhLBYFCjqtOnK+3RbNWqVcJgMIh33303w9WmX1fbI9d7UDrTHrfeequYOXNmm9v5/X4BQLzzzjtalJ1WVVVVYsKECUKSJKEoiujRo4fYsGFDy+XvvvuukGVZvPzyyyIWi4lDhw6JCy+8UAAQL7/8soaVp8fZ2kMIIbZs2SIGDhwoZFkWsiyLoUOHiv3792tUcXp1pj1aGz58uLj99tszWGFmna09Fi1aJIxGoxg6dKhYsmSJWL16tZg+fboYOnRol3pgdd2Dcu+995524FHz144dO3DOOefghRdewO9+9zvYbDZUVFSgf//+KC8vb7fl86OPPooNGzbg3//+N/bs2YMFCxZo9Oy6Lh3tAQBbt27FNddcg/vvvx8zZ87U4Jl1T7raI1uxPdrqbHsIIXDHHXegrKwMH3/8MT799FNce+21uOqqq3D06FEAwMyZM/Hwww/jtttug9lsxpAhQ3DFFVcAQNa0WSrbIxgM4pZbbsHUqVOxZs0arFq1CiNHjsScOXMQDAY1fqadk8r2aG316tX44osvcMstt2jwrLovle2hqiqi0Sh+//vfY9asWTj//PPxt7/9Dbt37+5wMO3p6Hqp+5qaGpw4ceKM1xkwYABMJlPL78ePH4fdbockSXC5XHjllVfwta99rcPbrly5EhdeeCGOHDmCHj16pLT2dEhHe2zfvh2XXnopvve97+FXv/pV2mpPh3T9ffziF7/A66+/jo0bN6aj7LRJZXvcd999eOONN9q0wb59+zBgwABs2LAB48aNS9fTSJnOtsfHH3+MmTNnor6+vs228YMHD8Ytt9zSZiCsEAJHjx5FYWEh9u/fjxEjRuDTTz/Fueeem7bnkSqpbI9nn30WP/3pT3H06NGWgBaJRFBYWIhnn30WX//619P6XFIhHX8fAHDLLbdgw4YN+Pzzz9NSd7qksj3+8pe/4Oabb0ZVVRV69erVcp3y8nI8+OCDuPXWWztVk6F7TyUzSktLUVpa2qXbNJ8zf+6552CxWHDZZZed9rqqqgJInF/OBqluj23btmHatGm46aabsi6cAOn/+8g2qWyPyZMn41e/+hWqq6tbZiEsXboULpcLI0aMSG3hadLZ9ggEAgDa94TIstzyGtFMkiRUVlYCAP72t7+hd+/eGD9+fIoqTq9UtkcgEIAsy5Akqc3lkiS1azO9Ssffh8/nw9///ncsWrQodYVmSCrbY+rUqQCAnTt3tgSUuro61NbWom/fvp0vKqUnpjT0+OOPi/Xr14udO3eKJ554QlitVvHYY4+1XP7222+L5557TmzZskXs27dPvPXWW2L48OFi6tSpGladPmdrjy1btojS0lLxrW99Sxw9erTlq7q6WsOq0+ds7SGEELt37xaff/65+MEPfiCGDBkiPv/8c/H555/n3KwVIc7eHrFYTIwcOVLMnDlTbNy4USxZskSUlpaKhQsXalh1etTU1Iji4mLxla98RWzcuFHs3LlT/PjHPxZGo1Fs3Lix5Xq/+c1vxObNm8XWrVvFL3/5S2E0GsW//vUv7QpPk860xxdffCHMZrO4/fbbxfbt28XWrVvFt771LeF2u8WRI0c0fgap1dm/DyGE+POf/ywsFouor6/XptgM6Gx7XHPNNeKcc84Rq1atElu2bBFXXnmlGDFihIhEIp1+rJwJKN/+9rdFUVGRMJlMYvTo0e2mdy1fvlxMnjxZuN1uYbFYxODBg8U999yTs39IZ2uP+++/XwBo99W3b19tCk6zs7WHEEJcfPHFHbbJvn37Ml9wmnWmPfbv3y8uv/xyYbVaRUlJifjRj34kotGoBtWm37p168TMmTNFUVGRcDqd4vzzz283GPjSSy9tef2YNGlSTg4WbtaZ9njvvffE1KlThdvtFoWFhWLatGli9erVGlWcXp1pDyGEmDx5svjmN7+pQYWZ1Zn2aGxsFDfffLMoKCgQRUVF4rrrrmszLb0zdD0GhYiIiPJTdgw/JyIiorzCgEJERES6w4BCREREusOAQkRERLrDgEJERES6w4BCREREusOAQkRERLrDgEJERES6w4BCREREusOAQkRERLrDgEJERES6w4BCREREuvP/A67vZBxCRQUzAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below I plot these again by county no, with faded neighboring counties\n",
      "0   [18, 20, 37, 42, 33, 43, 63, 39]\n",
      "1   [29]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are 736714.75 184178\n",
      "You may suggest [ [18,20], [29], [15,1,3,6,65,57,25,50,63],[14,30, 37], [21] ] \n",
      "let's decide whether to delete, accept, or modify list [18, 20, 37, 42, 33, 43, 63, 39] with pop 179212.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [18,20]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [18, 20, 37, 42, 33, 43, 63, 39] with [18, 20]\n",
      "let's decide whether to delete, accept, or modify list [29] with pop 169151.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 1\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [15,1,3,6,65,57,25,50,63]\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [14,30,37]\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [21]\n",
      "enter 1 if you want to manually add another corner-county cluster 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our final pops and fused-county lists are...\n",
      "13737.0 [18, 20]\n",
      "169151.0 [29]\n",
      "171003.0 [15, 1, 3, 6, 65, 57, 25, 50, 63]\n",
      "92501.0 [14, 30, 37]\n",
      "51938.0 [21]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Pb7WzamuU30/VZ59R/saHeLcdRHc5iD8rj9TrrsY9bFhY6gq1oERm8b9Id0AFMIIGb//ulwBMumpKp/Y1a9YsNmzYwBdffNFi+wdbitiVoPG7uPQ2jXh6ZvdhjHIvv5gxEr2LDeEWQohjSUCJUTXLlnHklXl4Nx8AI4jmcpB1z/dInnHpCV9TX1BA2etvUvVpQ9+S3AyyfnIdSdMvQY+LC2t9CtAi1IISyQ6ojb6ctxCAUVOuJy27Z4f3c9ddd/Hee++xdOlScnJyWjz25x0H6YXBjefmnODVR+2u9bFi5QFGjMtmWIKnw/UIIUSskIASY5TfT7CqigOz/4gjI5GMH8zEnp5B5cJPKfrjq9SsWEnPB36O7naHnq8UNUuXUvp/b+Hdceho35Lrr8YdxhaH4+oE9Aj1QWlrB9TOqCkrA2D8ZdM79HqlFD/5yU+YP38+ixcvpn///i0ez99bytoEuF9PxnaKIKeU4ner9hBMdHLPwI6HJSGEiCUSUGJE9eefc/iPL2FU1qL8ATS7i+zHHsA1aBAAidOmUvbaPI784x32fO/H9Jz9E2qWL6N6yWoCh6uw904l6+5vk3TJxeieyP8FHskWlGOdqANqZ5xx5VQ2Ln6VL197n2/de3O7Xz9r1izmzp3LO++8Q2JiIocOHQIgOTkZj8fDH9bvJ8lmcOeFfU65r/mHy6goqOQH0/KIt0XmspkQQliNBJQY4N20icL//jNGRQEpV81AT09Hs9lxDjy6AJ+maaTdcB1x48ZQOPsx9t87B03TcfRNJfu39xF3+sSoTj2vAF2P/IfpiTqgdlZqz0wSMvLYt34Z0P6A8swzzwBw/vnnt9j+4osvct5l1/C5O8hNKp44l+Ok+ynzB3hz+V4y8tKZki6rewshug8JKDFAc7mwpycRIJfq5ZsZ+P6/Thg23Hl59H/t71S89z7K5yP1huujXG2I0qIzk+yJOqCGQ4/+Q9mZ/58OvVYpdcLHZn24CbsN7mvDSJzHN+3Hbyh+NUJWKhZCdC+xPQ60i1GGQfmbbxGsrGyx3Zmbi2tYDpruwJmdccqWEM3hIOXKK0wLJ9A4zDiyLSiNHVA/++yz4zqghkNFUSE2Z3hbLSrq6nlf9zE14CAz8eTzmHxdXs2eTcVMPz2XHqdoaRFCiK5GWlAsxLd9ByUvLubwY0/hGjYA99DBxE08jdqv86ldsYekS08j6957zC7zlJRhgKZFrAXlVB1Qw+HjF9+mZO9Keg+/IKz7/XP+Pnx2+K+RJ+97Um8Y/HXFbvTeCdzUW6azF0J0PxJQrCQYwKgsBN1B/a4S6vdWULngG9BAj3OQdvNNbZ7rxEyGYQCRa0E5VQfUzqipqOb1Xz9O6YFvSO09jit+9oNwlAyAP2gwt6aKM3waw3qfvGXm2T1FeCt8/M/kQdhkzhMhRDdk/U+7biTUb0GR+/SjuIYOw6ipARTKH8Cekd40dNjqjGAQiFwflJN1QL3llls6vN9tyzfwwdO/J+ivZMy0W5ly21Vh7Vj8f+sLKXNr3JVz8qHCe+p8LP9mP8PH9mSEzHkihOimJKBYSUO/Sj0uDltCPLaE8Ew6Fm0qEAAi14Jysg6oHbV07vvkv/N3HO4Mrnjgd/QbPTis+1dK8ezBEobUGUw5v8dJn/e7lXsIJDj4r4G9wlqDEELEEgkoVtL4wRvjTfpGwA+AFiNzdnz28jus+uAfJPccw/f+91e44sPfarFoXyl73fBYXOpJW2XeaZjz5PapQ2TOEyFEtyajeCwl8gFlzpw5TJw4kcTERLKysrjiiivYunVrWI9hRLgFJZy+fncxqz54jtTe47nlDw9HJJwA/HlLIT0rgnznjBMPFy73B3h9xV7SB6cyLSM5InUIIUSskIBiJVFoQWlcx2b58uUsWrQIv9/PtGnTqKmpCdsxlL+hBSUKE7V11o5vVqLbErn5d/+DPYIdkHcG/Uyyu3C6T3yM3289QF19kAdG9Y1YHUIIESvkEo+VNPWtiFxAicY6NqphFE80JmrrLKUUms2BzR7ZMBUEPCcJJwCHd5axOcVGuuPo814/VMqXZdX898BeZDplLhQhRPchAcVKmlpQonfISKxjQ0NAIQYCSn1tACMQ/k63xzI0sJ3iH/bS0/tgfLqTW1dt54zMZNZU1ZL6dTEJhuIH64u4+uz+fDc7PeK1CiGEFVj/E6QbaRydEq01cyK1js3RFhTrd/atKK4jGolQaWA7xWGu6pWGY0wGvdeW8cXyfdRtLmVdtovhlw5CB55Yv49l5dW8U1SGEYGRTEIIYSXSgmIlTVd4ovPBHrF1bBrmQUGzfv5N6eGh9EDkj9OWFhSAJ4b1ZX5aEvelJzVNb1/mD/BRQDGgPMhz72+mV51B0cUDODctkb11PqamJ0V1IUghhIgGCShWoqJ3aaRxHZulS5eGfR0bPS4OgIp9e8O630jQbQoVLMUIBNEj2A9FNyCgnbrVw2PT+c4xl3FSHXYuu3Agpf4Ae+vqKcw/SMHne1hg1+hda/B4loPXp44ixSH/OQshug55R7OSKIziicY6NnFZoYnIVAxc4nHHJwDg9wdwRTCg2A3wd+J0XNvzaB+ht5PjKfT5GRjnYk1lLYX5B3hhXzH3ycRuQoguRAKKhURj9Esk17FppGkatsaOshaX0rMHBRsiP2eLLajwh2lfV/RIbbp9cUYy/xsw2LhsPw/6/Pxm+MkXIRRCiFhh/U4C3YnRONd95P5ZnnnmGSoqKjj//PPp1atX09drr70W/oPFQkdOZQBaxPtwRHLvvxiUzSc97PiWHeTtg6URPJIQQkSPBBQraeyDEsHOpUqpVr86s8jeyY5ldYro1Gi0YRTPqZxoFmC7rvHRWcP4PMvOH7/ezZaauvAULYQQJpKAYiFNl3is33Wj61AQjWHGbR3FczInmwV4SLybH47pQ16VwSOrrd85WQghTkX6oFhJFC7xRFUMtKCEEopGpBtSDE3D3skcdKpZgG/qk8k/847Qa1sV5WcEZFSPECKmdZFPwq6ia6xmHEuicRlKKYWhgR7mlprWZgH+f4NziA8qzvl8Y1iPJYQQ0SYBxUqiMMw4qmKhBSUaNSow9M73QWnuRLMAn5GSwI6hSUw4WM/LB0rCd0AhhIgyCShWEoXFAqMlVn6ChsUFIn4MQwN7GI/TOAvwq6++etxj/5kwhK1JOq8u34M3GBvDvYUQ4lgSUCwkFka9dD0NfVAieQSlMDQtbC0ojbMAf/bZZ63OAuzSde44rS85dYo/7TwYnoMKIUSUSUCxEhNWM+72oniJx97JS3dKKe666y7mz5/Pp59+etJZgG/tncHueJ0Fmw9xpD7QqeMKIYQZpJu/lTR1QekaCSUWWoRCNUa+BUWFYZhxe2cBTk53E7e/ljveXkOq005Sr3j6ZSUyJjmO0YlxpMkoHyGEhck7lKV0tU6yZhdwakbAAE1Dt0dwcjxDYeidH2b8zDPPAHD++ee32P7iiy+2OtHeG+cMZ09dPWurallfUcvhA5XkrzrAkmDoHybNZSepVwIDshIYmxzPmMQ4EiO4HpEQQrSHBBQr6WqjeGIgofjrg2iAHsGFDRvyQKf7oLS3RUrTNPrHuegf5wqt3zOkN4ZS7KmrZ11VLWsraji8v5Iv9x3gU0OhAddVfM452jqyhwyHXuMgeyzEZ3SucCGE6AAJKFbS1QKK9fMJvpoaNJszoseob5ghOGCBzkW6pjEgzsWAptACQaXYXutlbWUdo+b+hIyKOuoKS8D/IQBafBqO3qnY+g6R0CKEiBoJKBaiulRA0WIhnxCor0O3hWcV5xOpDoQCylcBL/8V0SN1jE3TGBrvYWi8hy12O6sGjuHM770IZbvh4BrU/rX49x6gfvHSZqEltSG05EloEUJEhAQUK2mY6l7rKlPdx0BEcSckEPRHdnE9vSF4TrC7InqcsFEqtNxC+kBIH4g28mqcjdtLd506tPTJg2wJLUKIzpGAYiVdqgUl8qNjwsGTmIQy6lBKRWz0VLAheP6tuoKv3l0LhM5M4xcaaApOS/TwPxcMiUgNbaVOdgo0rfXQUrYbCleHQsueQuqXLoX6xtCSgqN3WkNoGQu9xkJCZuR/ECFEzJOAYiFawwgKFQyaXEmYWD+fYHO4gMjOE5KV5Obsap1SZVCD0dSupBq+ULA1UWOTt5r/iWglp6a199KcpkHaAEgb0EpoWYM6sBb/7gNNoUVDQVNLy1AJLUKIE5KAYiGqoTNlV5kHJQau8ETlnDtsOm9cPvqkz/nxh5tYbHgjVkNbGYSh91CL0HLVCUJL4TGhJQVHThq2XAktQogQCShW0rQUT+wHFC02rvCglIE1JlRWljlfESnjVKFl/7oWl4eaQkvvVGx9hkloEaIbkoBiJaphYbcu00k2BqhQm4HZlGoIdaaLzrmYM2cOb731Flu2bMHj8XDWWWfx29/+lrwhQ6BsT0OfltZCS3Kz0DJOQosQXZgEFCsxGj4su0ALSqxQVgkoYIUyGkQ+KS1ZsoRZs2YxceJEAoEADzzwANOmTWPTpk3Ep/WHtP7HtLTsCY0eKliHf88B6pd+DvULmkKLs3cqep9hocCSPRYSsiL+MwghIksCioUEq3VcY27kwK8WtRJStJPcPXon33WA3fpBMOpDG1TT/7W2l2bPacPzmp526uf1nFlHdfyHfPj2wtCzTnjJ50R7UA2vMdA0BZpxtIlBNRsD03hb6Q3b9Gbb9ab7WtNtvcXz/Ym19JxgiaYLKh0a099vGOXTrCetBqAUcZrO387PIz0xcsOVFRpaFNZQWrBgQYv7L730EllZWaxcuZJzzz235ZM1DRpDy4grWw0t9XsKMZqHlrgknDmp6H2GS2gRIkZJQLEQe+88bPH70d0HOe6v2Db+dX0oWItTj6Ov093Ko9px+1Un2rHW8b+jFRCXdQjDl4JT5QLG0fpPuFPV4pamaWi6BtjQNBugo2EDFAoDhQHKQKkgYKCUgSLYsM0IbcMAgk2vCW0LhD7AtNAYGndaDYl9qjEMP7ru6OBP3HkzslPZveswQc1o0ZrSOOz3gF1RFgerCiuYmhe5D1plUutdRUUFAGlpaW17wTGhxQUtQotRsA7/noMtQosWl4SjMbTkTIT+54Iuaw8JYVUSUCzElhAPQM/ZV6O7OvbGqT3yBL0Ss5h59/fCWVq7LVj4T+KTz+O88x4ztY5T+WbJP6gIzsHshZcvH5vN5WOzT/j44k1F3HC4EEcXXMzPMAzuueceJk+ezMiRIzu+o2ahRW8eWsr3QuHqptCiln6Oql+InpiAc9IFaONvgrg2BiMhRNRIQOliFKH1VqzBMLuAUztly45F6I3folBolNParFmz2LBhA1988UX4d65pkNoPUvu1DC0HVhL86v/wfrwQPl6Aa/Rg9DNvhd6nhb8GIUSHSECxEKOuYYK2TuQLFepFEJ6COkuz/mikWMknNKy2rIKRrVS1f6q2Trnrrrt47733WLp0KTk5OdE5qKZBzgRs103AU1OC+uYVfMu+RK25H0evBOyTr4fhV4CjtcukQohokYBiIXUbS0I3OvEXbCSnbG8fy3/kh1jhVLVBkjP0n2pFfWRnvY1WHxSlFD/5yU+YP38+ixcvpn///lE57nHiM9DOuw/3OXfDtoXUfz6fujeeR/c8j3PiZLSJt0FKH3NqE6Kbk4BiAb5d5VQuLsC3vRwAzd7xlgdlqTVwrN+CEitNKL08oQ68h/2RDSgQnXWoZ82axdy5c3nnnXdITEzk0KFDACQnJ+PxRHZ16VbpNhh6Kc6hl0LJDoJfvoJ32WpYegvu/kloF/4c+p4lUwAIEUUSUEwWKKmj+B/rsae5SbgwF8+QVDRbZwKKNd5DNc1Cl5pOoi7wEQCGEQDMG8VzKolOB3pQURmI/DpNJxzZFUbPPPMMAOeff36L7S+++CK33HJLxI9/UhmDsM38DZ6xX6Je+Ba+/RNRzz+Mo4cL+9k3wsirIFZWphYihnXqT9zHHnsMTdO45557WmxftmwZF154IfHx8SQlJXHuuedSVxfZJe1jVeXSAjSHTo+7x5MyrR+ufslmlxRG1g8oDtvghlvWHh1jc2ihod8R7oMSLUqpVr9MDyfNaTY0LYD7/Kl4br4fw5VD3ZsvUP+7y1FLHgejISz666C2FIKRb90SojvpcAtKfn4+zz77LKNHt1wEbdmyZVxyySXMnj2bv/zlL9jtdtauXYvezadvr9t8hJr8wxi+AHGjM4kbnYnmslG/swJH7wQ0R7jOT8cv8Zxw+vG8vA7VocVAJ1k7/QDQbRYPKPbQ+B1lRDagRGOStpihGgKIboNBF+EcdBEUbyP4+YvUfbwEfelnOHto1BeUEyQTl74O29hLUJoLze5Am3gTJPSE+PTjd60UXr+Bx3n09+6rnSXU+oIM6ZFIn/S4aP2UQlhWhwJKdXU1N954I8899xyPPPJIi8fuvfdefvrTn/LLX/6yaVvHPuC6jur8g5S/uQNbpgfdbaN8/g7K5+8Auw4Bg9SL+4b1eB1ttzjp9OPx8e2rIUZWCwwGQ0OhbZ24rBYNul1DaWBEoQUlGpd4YkJjGGw+mVvmEGxXzSHu9JWoNf/Gu2ItGg5sHMEbPBPbqp3oaRkYpcUElhdi1woptiez/JwHuO7CCQAEDcUvX1nJni0leAal4CmqwxYER42fQxgYwAM/PoNxfVKj/zMLYSEdCiizZs1ixowZXHTRRS0CSlFREStWrODGG2/krLPOYufOnQwdOpRHH32Us88+u9V9+Xw+fD5f0/3KysqOlGRZRq2fig924xqSSsatI9A0jUCFD+/WUoJlPuwZHuJGhW+xM9WJTijtmn68TSL7QReOFh8jGGhY/sjaH8q+oAGahtvidXYpqvGSTSvnPGc8Ws54PBd7Q/1R9i0HbwUMvCB0f9cS1CePUh3fh95bF7Hho00MGzKYkb2TmPv1Pg5vOcIBDAbuqiRjdBZx8Q56p8UxdURPfvrYEu5+ZSX9E1y464KMnpjNtyf1Iy3eCcChCi82XSMzgkseCGEF7Q4or776KqtWrSI/P/+4x3bt2gXAww8/zOOPP87YsWN55ZVXmDJlChs2bGDw4MHHvWbOnDn8+te/7kDp1uPbU0Hlx3vRnHbcA5Nx9k+m9LWtqLogKZcPQNO0MF9Gad22kt189c5izpp5fqf20+7px5vR9SDVNa/j9f4CtzsyzdXhaPHRtFAz/mfv/fzYR4753ny7goap88FgT008nxeOgmDvpmd9WlKBDpyfEepTpE5x6eRkjyoF9YaBPd7gL1o572w7fMp9tvaIAob5tnCtsYjEhNB/+kl1xQw9vIzC5MGUJOTSp3I72+J7nrTWLuX1m6FwdbMNzVr+vOWh7ycLhY1zpfSd1HL7gPPQBpzHoVWfMXjbW5yr1fDoU8tJtdsoDQRwux18+quLMJQiztnybfjb14zgnbc2U1ddwzcECXy8my8/3cPIyTkE/Abbvy7EMBS9hmfww0vyGJSV0JkzIIRltSugFBQUcPfdd7No0SLc7uMnMTKMUHP5nXfeya233grAuHHj+OSTT3jhhReYM2fOca+ZPXs29913X9P9yspKcnNz2/VDWEH1ioOUv70De5ob7H7Ktxxpmkg17oyeODJDH9LhvIzSmonDxrFo4+ds3rSpUwGls9OPV1RkkZJymIMHt9K//7gO13Ey4Wjxyew5jvKduaCt4OjH+rHrILWyXekNCw7qLCk6hy+LXWRR3eJlBrC1tJrGD7xTtX2c6vG4gAYOnQO1Rztjnvg1rYyh0uCWmo84i0/YFRwGmkaSNzT3TnxdMQdcWWxOPw1jxFWnqKQL2fwuKANcSc02Nht7HpcBAy7s8O4zc4cC0NvxNJdc/B/Kav1kp7gZ1ycVt6P1fk/XTMjlklG9sGkaLrvOhsIKHnxtHe8/+TTr8t+krqaMXv3zGFvxQx7aVMKA8T359uT+DM8O/QyGofhmbxmpcQ4G90jscO1CmK1dAWXlypUUFRVx2mlHp4MOBoMsXbqUp556iq1btwIwfPjwFq8bNmwY+/bta3WfLpcLlyt2myoNXwDvplLK5+/A0SeRrDvHoNk0lD9IfUEVhjeIe+jRFojwX0ZpafK1U9i9dw9ev+/UTz6Jzk4/PmjQTygp+W/i46PX2a8jLT4Dhp/DgOGLO3Xc1597mYGpxSz4+R2d2k80LPvraxSV9GDE3UtbbE8GJppTksk0yD0Tbl8Ykb2nZPbik8RvMcS3gVsmt30yugTX0bfm0Tkp3NC7kJuX/IOnnv4rk8+axBNPPMG8V3/Fbb9/i7qVRfxl5WFIc5PSO5Eju8qprqnHZ4Nf3Xk6B8u9fLP7CKf1S2Pq8B4nDEZCWE27AsqUKVNYv359i2233norQ4cO5f7772fAgAFkZ2c3BZVG27ZtY/r06Z2v1gICpV78xbUEy31UrzhIoKgWAgpbupvEC3PRbA1/LTtsuAaknHJ/nbmMciKh/hQd70wZjunH9aYRPNFZjydsC851QCAIDj0G1h0CDOzYYmGNpC6kbe1nJ/enP/2JO+64gzu+fzsAf/vb33j//ffJKF6O6/wrqQ0YVJTWUXeomt7DM+idFc9HH+7gt39dAUCcprNt2QGeYR2TJ+VyxcQcRmR3pSkNRFfUroCSmJh43Jt/fHw86enpTdt//vOf89BDDzFmzBjGjh3Lyy+/zJYtW3jjjTfCV7UJjFo/lUv2U71kf9M2Z/8kkqf2xTMmC3tK+1uBIvWhqmtah2bLD+f045pma9pnNER0wblTsNbsvSdnaDo6kZ/sTRyloTA68ftRX1/PypUrmT17dtM2Xde56KKLWL58Oe80297cjWf0ZXdJDS6HTnayh53F1Tzz9kY2LdvP9mX78QxKYXxeJmcPzmBoz6RW9yGEmcI+k+w999yD1+vl3nvvpbS0lDFjxrBo0SIGDhwY7kNFTf3+KoqfX4/yKxx9E4k7LYv40Vnons6dvsh9qGoNH5rtryds0483dCxUKvIfhqYsONeCipmhuUrT0ZW0oEST1snfj5KSEoLBID169GixvUePHmzZsuWEr/M4bU39UgBG9k7m6VlnUeMLMPvNdZSuK+bjHeUs0XfwxAPnkZ4Qu5faRdfU6YCyePHi47b98pe/bDEPSqyqP1BN1ZIC6taVgF2jxz3jcWSEZ52QSH6oalrHWi7COf144yRtKoIfhlZZcE6LpRYUbGSoI/C3c45ubBqlorXtPtB0CVGpdt5v9vrmjx13u9nrlQGGHwL1EPRB0A/1DR2Sf7AYsk/QCXvxb2Htv8GVCHZ3aPhvi+/uo5OxRZDeoT8XIifeZefP3zkN4wbF9/5nEc7cRJI91l3mQXRfshbPCdTvr6Lo2XXoLhuJF/clcVI2urvzpysaH6qa1rG3xPBejmlsQYlcQLHSgnNW+gA6mY1pF1FeepgrcnudPEycNGi0Mci06f5Jbjcf3mt3gc0Z+rK7QnOOLPktVB068Q9bsALKdsPE70PACwHf0e++ytB3mwsSIzusOtQjrOMTAWZkZGCz2Th8+HCL7YcPH6Znz47XrusayWkeCsrqeOmrPVw/MZdEtwQVYR0SUFoRrKyn+Pn1ODI8ZP5wDLorfL3eo/GhqhG9vh8noje1oESuDqssOKdpsTP7aomnH+947uSKGeeZXUrnVB4MBZSSbZDSFxwecCaAMz50W9PAnQT9z4UZfzjxfp6aCMmRvSyoa527xON0Ohk/fjyffPIJV1xxBRDqv/bJJ59w1113daq2aef35835m1n//g42birmT3ee0an9CRFOElBaUfP1QVRdkIz/GhnWcAJR+lC1wGyjRzvJRq4J3ewQ1kiD2GlC6SocHtAdsOjB0FcLWiio1FdDz9GtvrxJFH6HfP4A9Z1couC+++7j5ptvZsKECZx++uk88cQT1NTUNM031VFnDcngnWQXlUfqOHNoRqf2JUS4SUA5RvWqw1Qu2Y8jOx5bgjPs+4/Gh2rnBhmHqYYo9EGxjE7+hRxtFsl1neNJgVkroKYkFMj9tVBfC/U14K8Jfa+vPXH/lCgqqfKR3Mlh6Ndffz3FxcU8+OCDHDp0iLFjx7JgwYLjOs62x5qCcv748moMw+Dh+ybLjLTCciSgNOPbU0H569twDU4h7ZohZpfTYZoFIkpjQDGi0AnRbOaf7bYLGgq7xRdGbLP0gaGvzopwi2OKx4bN3/lzftddd3X6kk6jefn7eH/+FlyZHn596wSyU6LbZ0uItugi71Th0dgJNn5CT2zJMTzkTjP/A1PTu08LSjgv8cyZM4eJEyeSmJhIVlYWV1xxxXETH3ZGwFDY9dhp7Ym8yP+Xkuyx43Fa62/Bhe9tZ70R4L4bxkg4EZYlAaWZui2lAKj62P6rX9M00/tnaFEYxWMVWhgDYeNaTcuXL2fRokX4/X6mTZtGTU1NWPYfCBrYJKCE3dNPP02/fv1wu92cccYZfP3110cfVNa7BDj98iGMsDt49MllLNhwsGl7MGBQtLeSnauLWL1oH1+8vo2ais4tmyFER1kr1pvIX1RL5YI9xJ/dm7gJHb+uKxo0TdRmdltOdCgVng+gSK/VFDAUDpu1PizN17nz8dprr3Hffffxt7/9jTPOOIMnnniCiy++mK1bt5KVldXpidoi4eoJucwYk80P/vwVr85dz8LcvWQ5neRsrSGxLoBfgc2uYQsqVlTWc+H3o7t8hBAgLShNatcWgU0j5ZJ+DWvZxK7OrsUTlhos9oYcSZH8dQn3Wk1BQ6HH+O93WIUhQP/xj3/kjjvu4NZbb2X48OH87W9/Iy4ujhdeeAGw7kR+boeNZ+6axKRpA0DTSFhXBtV+ci7px/T/dxZX/PE8ag0oXlPM3o1HAKj3BggGDQyje/zhIczV7VtQlFJUfryPqk8L8IzJRLN3jcxmlbeP7hRUwi1SazVJPgmfk62Ts2zZMqBhLR6LnvR4l507zx8E5w/i0Z8tpjrZxvdmHJ08csTVg9ixcA8r/7aOVQ4bgYbL37qu4c5JIG1wCiPO6U1SmGbYFqK5bhtQVFBRv7eC8vd34z9QTcL5OSRP7Wd2WWGhYX4flKOHt0pUij2RWKtJ1zSMrt8tqH06ER7ask6OVVtQjqM4rvV49IW5jLoghx0ri6g64sWd4KC+LkDx7kqC5V72f1LAno8LuOGp82O+5VlYT7cLKEopqpcVUvnRXpQ3iC3VRcZtI3EPSe30vv1FtRQ/uw4VNNB0DXQNzdYwZXdDx8TQLN5a6P2q8TYNbwwaTc8LzfStHX1O0yzhoX0mTemDq3/ry6Vb6Y3CSrVEUrhjWKTWatI1jWA36RfUNlE4F0oxwreGZX/9YdN/zxoaqmFKf9VsWv9QNQ3bmx4Hb20KBd7TqPH0RLdpaLqGbtPQdQ2bTUO36eg2DZuuh/qO2HQcdh2Xy4bLZcPtseNxN3x5HMTH2Yj3OHC77eiNw86VOvr+04ymaQw+Qb+8rSsOseWfm/ni1W2cPnMArjiZKl+ET7cLKL7t5VS8uwtH73iSL+mPa2BKKEyEQbDMi1HjJ/GCXDSXDYIKZShovF6rVLO10EK3j25rtpha02MN2495fu2GI/h2lp8woDTuxgrMbsmJhtD7enh+zkiv1WTTwegG/ybR0pZ1cow+kynYvI3eJUsbhqSrhljSGEeOfj/2dmNsWVN2E16vkzpbBboCTTX8PdP4HdA72EoTRBHQIEVpVLfz77Qhp/egrsLHrg/38J9lB4nLimPkVQPpMzy9Q7UI0Vy3CyjeHWVobhtZd40L+1/3je/7CZOysSWFfxbaRt5Hl5/0cc0Cc68fPbdd/8NQKRW236VIr9UUusTT9f9N2iey6+RMvO4XwC86VaF66Hl6uwqZ+dtbTvicYMDAHzTw+w18/iDe+gB1dUFq6/zUeYPUeQP4vAG83iD19QHqfUHqfUH8viC2eoNAfZALzs1tV12apjF2Wl8Gn96T3etKWP3aVr54eh3XPH4OTk+3+3gRYdbtfoO828pw9E6IzKWHxjf+SF/VUJz8urmmWSYWdIcWFKP1lvEOifRaTbquIfmkmTD8fkZqnZzm2lKmza5js+u4XZAYtiO3TXyKi5Hn9iYhxck3z23k/UdWMOXe06TzrOiUbhVQVMAgcLiWlG+FYXrsVg/Q8C4SjYmwTpZPLDD5enfpewINASVM+4p0oNO10FBjET6RWCfneMryo68qims5vLsSvw5xVX52ry1hzJT2tcgI0Vy3Cii+3RWgwNEjDsMXINQTtXlnVJo6pHboA7axASUqLSgnfljTrLAgXPNOf12bipFBGgA2TZM+KM2V7YY9nR8lFc51cloTC/9kXz63gfqDNWTkpdFnYg8GjM00uyQR47pVQKnbHJpsqPjv69v3Qq2120dH2Gg6LVNBxGfqVNR8fQjvtrJWE0CgqI4KVXN0oihNawpczb93ZFtbbgP4A7tIS4Pior9RWzsfTdPR0GlIf6FWHk1v7DGMwmj4WRQKBcoIfW/oVXz0dsMY2Yb9KYxjntO6FvOxNCXIVv9hjz73hElTa/E8nz8HmxYbnQI1CSjHO/CN2RWcmrL+/DW6w4Zf0xh6YS65w8MzsaDo3rpVQIkbl4U91Y0tyUXoQ+3oNwzV9AFJw2eganqQxg0tbygaRukQ+oA0FLZEJ7orsqc18fxc/IXN1mY55o1rmGcIgXoHthR3qMyGDySlVIvbJ9tmNEyW0ZbXtHYbXLjdw0hOduD3lwGqYV2exjBhhMJGw1BKDb3pNjSuhtwQZFqEmoYf1lANE4g3btNbPt7sQ/hodGk2UqrpdsvnHafp8daeF/qu60Nx2WMjoNikD0pLqf1h+Eyzq+gSzvnBSJb8YwPfvLAB10/GktU3yeySRIzrVgHF2SsBVRcMy5wnZko85+TzYqQBQ5kUnWJOapbZBURF8oaV1PljY4FJXUNG8TRngWUh2sJqa/m0Jj7ZxYV3jmbh49/wxeMrybt2MCPODd8cPqL76RrzureVbonOGaKLMZSKSr/ocNDlEk9sipF/MneCg0t+MYH6JCf7lhwwuxwR47pXQNFi5r9zEUNCw4xjJKHIfwPHiI0/Wk41s4CV1HuDuGoDuHrFmV2KiHHd6hKPpmmougD1B6px9IhrsTBgsMZPsMKHo0d8aHp6IdoonBO1RVponSazq7CaWDkh1q2zqtTLVy9uJC47gdoaPwG/wcSrBptdlohx3SqgAMSNzSJYVY9vbyUEGjuCgi3egS3ZiXfzEWypbpy9E0yuVMQKQykcMXKNR9NO0Bm4u4qRYKksvi74gW1lBPZWcXB3JRqQkpdKYprb7LJEjOt2AQXAlujEltj6VPSekS4CpV5q1xXjHpqG7rRFuToRaxSxc4lHIyauaERXLJwQi8+1M3h8D8oO1OBfUkDqaVmcd8sIs0sSXUC3DCinYk9zo/xBjFq/BBRxSoYCPUZ6c1ljEj8rsfCnfgyxOXQmXT2IT6vrKV9XYnY5oouIkbdVcxi1AbNLEDFAAxqmjbE8a18oECeilIauWf+XrPfQNPy+IEcOVJtdiugCJKCcgKNHPCpgUH+w5tRPFt2a065TH7T+hwc0tqBIE0qTGGlSUugxUWffkekoYM37u80uRXQBElBOwtUnCaOqnmCN3+xShIXpMfShH5rq3uwqRHsppdCi0BH7mWeeYfTo0SQlJZGUlMSkSZP48MMP2/z6soM12DToOUymuhedJ31QTsE1OIW6tcV4RmdG5Q1CiEjSZRTPMTTY9xUsejC09IJSDV+NyzIYkDUMJtxmbpXKQBH5/nA5OTk89thjDB48GKUUL7/8MjNnzmT16tWMGHHyjq9VpV6+fHEjeryDvDN7RrxW0fVJQDkFTdPwjMjAu7UUFLgHp6I5pOFJxCaZB+UY/c+FHR/D5veOrgWlNawLpelQtAkcceYHFIIozRHx41x++eUt7j/66KM888wzLF++/IQBxQgafP3uLvZ/UoACTv/JWOyO2Bxc4Df8lNSGOvkeO7eR1rRO2NHFQtv0nGbb7LqdeEd85H6ALkYCShtoDh3PsHRU0MC7oxxPnjRfitika8glnuZmPH7yxz99FNbMjU4tJxE0NKL9mR8MBpk3bx41NTVMmtT62l713gCLnlhN/YFqcqbkMmZqHzwJrU/hYHW+oI+fvXk3VcVlnW5lTA4mUGE7vqOwTdnIyO3FJeMu47yc87DpsRnkokUCSjtoNl3GQIiYpuuxsTieZfhrweExuwoMQyNan2Xr169n0qRJeL1eEhISmD9/PsOHD2/1uQe2luE9UM3om4YzeGKP6BQYIX9a9gcCxbVcf+ktJDuTG1ZBP2Yl9+armh+z7bj7qGYLqIdulPnKWLZmCXPf/Qdvxc9l7PgzuWrIVaS55Y/e1khAaScVlDd3EdukBaUdLBJQgoaGLUpLcOTl5bFmzRoqKip44403uPnmm1myZEmrISWzTyLoGgc3H4npgPLR7o/Yv2obF0y7jOn9p0f0WNcOuZaNJRt5c/088r9YwjefL6XX0P5cOfpqRmWMipllM6JBAko71B+sOeEMtELEAlnNuJ38XksEFMPQ0e3R6fvmdDoZNGgQAOPHjyc/P58nn3ySZ5999rjnKgW+gKJ8T+Up96sMReGOcuKSnKT2tE4/jIKqAt786J9kDu3NtXnXRuWYIzJGMOKCEZRPKmf+9vmsXPklf978GAkZKZw3firT+0/HbZelAiSgtJFvdwW6x44jN9HsUoQF7TlSy58/2Y5GQ/9KTQt9p/E7Le9roa5zQUNRHzQIBBUBw8AfVPiDBoGggd9QBIIGQSPUfBxUiqChUCr0OkOFvkK3aXY79BwFoYEoTU3QcLDCK51k28PwQ/k++OAXRzvOojX+Ize73bCdhlFATW37qtk2Gjrgnuyr9ecYRjxlVfFs/PwAuk1Dt+noNg2bTUe3a+g2jZQecSSlhz9MGYaBz+c7bruvLsCnz67HpcPoKweddB+HdleQ/68t+A7VomvQ95J+jJ/RP+y1tld9sJ7fffgoeGzcf/4DUW+9SHGncOuoW7lpxE18WfglH6x+l/cXzmOR812GjBvDtcOupXdC76jWZCUSUNqgvqAKbBoOC6V+YR1jclNYta+cV5btBY6GA6VCwUEp1SwsNNuOwqHr2G0adpuO0xa67bDp2PWG7zYNm6ah6xq6BjZdQ9dCX7aGbQ6bfnR7wza9aRRB4/+FwlG/jHiG9pSQ3Wb9zoHDm2DP583ChnHi2xwTXKDl7cYhzE1Dmo2WQ5qP+wptT3Hcxe4juRT+a+sJS03PSeCG/z69Uz/u7NmzmT59On369KGqqoq5c+eyePFiFi5ceNxzv5y3DfehGo6kuek3KuOE+9y1ppjVL2zEmeFm4o9GsyP/EAUL9lBTXMe5t7TetyVa/rziSQLFtfz0+vtJdJr334VNt3Fuzrmcm3Mu+yr3MW/T62xdtYbffP0N6f2zuXzslZzZ68xud/lHUxabYaqyspLk5GQqKipISkoyuxy828qwZ3qwp0pzmxDCXEoplKEwgke/gkGDJXO3Un64lu88fGan9n/77bfzySefcPDgQZKTkxk9ejT3338/U6dObfG8uup6Ppz9JZl2jf31ivE3D2PfN4cxvEGUL4Ce5MKZ7KKmpA7fznLih6Yx5YejsNl0lFJ8MW87Rz4/wOk/HUv24NRO1dxRb29/m48/fJszL7yI7478rik1nEytv5b3d73PFys/paa0grikBM6ccD7fGvQtEpwJZpfXqnB/fktAOYW6LaV4hkoPayGEdX32f5spOVDDtb+cEJXjKUOx9P82U3aohtp91STawGvTSemfjO6yUV9Sh+ENYBiKgZf0Y+jk7IYRZCG+ugDv/vxz+k3vx8QoX+oJGAGeXPEEu/M30nNUf351/v9YumVCKcXKwyt5Z+1bHN6xD5tuo++oPK4deT0DUwaaXV4L4f78lks8J6GUQtUHzS5DCCFOKuA3sEdxAklN1zjv5tDlmdKDNRzaVcHgiT1wtHH19y9e2Yxu0056aSgSSr2lPLLwYeoKKjh7yjS+M/w7lg4nEOqvNqHnBCb0nMDhsw/zxpZ5bFy9kjlr/oe03j24eHxoThW73vU+zrveTxQmyh+kbtMRXIPMaX4UQoi2CgYUepSGIR8rrVc8ab3a3j9v3af7qN5QQr9L+4WGKUfJxpKNPPn+79AC8P1r7mJiz4lRO3a49Ijvwazxd1E/tp5FexfxycoF/Pvd55kf/+8uOaeKBJRW1B+sIVhah2eUrL8jhLA+pVSLSyhWtWFxAbvn7yR9Ui9Ou7hfVI6plGLe1nl89sl7OLM8/Gr6w/RK6BWVY0eK0+ZkxoAZzBgwg41HNvLW+jdCc6p8EZpT5ZrR1zEi4+RrJ8UCCSjHqNt8BEdWHM4R0W16FEKIjlJGdFY77oz6ugDb3t1F6vgszv7O0OgcM1jP77/4LYfW7qLvaUO5b9LPcNq61lxWI9JHMOL8EZSdWcb87fNZ9c1X/GnToyRlpTFlwnSm9Z2Gwxb5dZwiQQLKMWQiNiFErImFgLLyw93gNxh/2YCoHK+4tpj/9+FD+A5XccklV3HlkCujclyzpLpTuW3Ubdw84maW7F/CglX/Yf4H/+ID91uMPG081wy9lsy4TLPLbBcJKMfQ3HYMn3SMFULEDsMAm4Xfzf2+IMWf7afcbiMpI/Iz864tXsvT//kDoHHXtT9ndOboiB/TKmy6jQv7XMiFfS5kZ/lO5m14jbUrlrN6+TJ6DunLVaOvYUzmGMt3DgYJKMcJlnpxD5GOsUKI2BHqgxK9UTzt9f5f1qABYy7uE9Hj7K7YzWvr/03B2m24eybwP9N/HXOtBuE0MGUgvzz7ASpPr+Sd7e+w4pulPLXld1R56phzzR8YkByd1qyOkoByDD3eQbDChy3ZZXYpQgjRJla+xFNfF0DtreSQX/GtaX3Dvn+lFMsPLued1W9RsvsATreLMWedya2jb+ty/U06KsmZxPdGfI+cxBye/uCPZNWmcaTuiASUWKPH2wmUS0ARQsQOZSjKDtVSdqgGm0PH7rBhc+jY7Bo2u25qc/62/MMYwLQ7R4U1RAWNIO/ufJfP8hdSW1pJfFoSl11yHdP7T8dlk/fv5g7VHOIvnz9B6fZC+vcbxE/Pu4/cpFyzyzolCSjH8O+vxjNSRvAIIWKH3WXjyLZy5j684oTP6Tkgiat/EZ2ZZhtVltSxed42nFkecoeHd36O17a8xteLPiV+UCo3XnArp/c8PSb6VURT0Ajy783/5vPPPwKHxhWXfZtL+l0SM+dJAsoxVNBSM/8LIcQpTb1tBOWHagkGggT8BsGAIug3CPpD91d/tI+iPVVRr8sV78Cma+Se0QuHq22zzLbVuq0r8fRPYc6M34d1v13FxpKNPPPJnwkU1dJ/3DB+fPpdJDnNXz6mPSSgHMPZNwnf3kpcfWPrH1II0X25PHZ69D/xe1ZdlZ91nxVEsaIQl8eOq0cc297ZRUbvBPqMSA/Lfmv9tZQcPMQFF1walv11JdX11TyT/zS7Vm/EluHmxzfE7igm63b7Nok9xYXhDZhdhhBChE0wYGCL4lo9zZ3zg1EkD0pm5d/WsfAvayjcXt7pfS4/uBxDBTmn9zmdL/AEnnnmGUaPHk1SUhJJSUlMmjSJDz/8MGLH6yylFB/t+Yif/fMudqzfyJnnTeGJ6/4as+EEpAWldXKVRwjRhQTqg9gd4b3E0lZJGR4uuXscm78qZOeifSz/yxpO//FocjqxSvyyvV+REp9Gn6TIDVvOycnhscceY/DgwSilePnll5k5cyarV69mxAhrTSN/oPoATy7+I5W7i0gZ1JO7z7kv5qfzBwkorVOSUIQQXUfQb14LCoRWPx5+dm/yJvXinV98Qf5bO+l1fwo2W/trUkpxaNse+gwfEoFKj7r88stb3H/00Ud55plnWL58uWUCiqEM5m6ay+dLP0Jz61w78xam9JlidllhIwGlFZpNJ1jjxxYfm+sXCCFEc0FDUVpYw4u/+ALdrmGz6dgcOudcN7hTLRntZbPpjP3uUNa9tIk3frOCwWdlk9ozjl4DU3AntO39dlvZNmq81Uzue3aEqz0qGAwyb948ampqmDRpUtSOezL7q/bzh49/i3d/BYNOG8GPT7+LeEfbV5WOBRJQmlGGwru9DN1tl3AihOgyxk7JJTnDgxEMjfAxggZrP9lP0d6qqAYUgAHjsqirrGff4v3sWbiHnfUGmgbuRCe6TcOR4SEuO57kHvGk9IgjJSuO+BRn09DYpQVLceluJvSI/JDp9evXM2nSJLxeLwkJCcyfP5/hw4dH/Lgno5TizW1v8vFn/wG3zm3X3MXpvU43taZIkYDSwF9cS+BwLa7BqehhHg4nhBBmSu0ZT2rPln9db1hywLTZZ0ecl8OI83JQSlFV6mX/ljJK91djGArvoRrK1xRTWFnYdLndZtdwp7pxZsZRWuUne9CAqMwSm5eXx5o1a6ioqOCNN97g5ptvZsmSJaaFlPpgPQ999N9U7igiZ/RA7pl0HwnOBFNqiQYJKECg1ItR45cJ2oQQ3YahQDd5enxN00hK9zB88vELCAaDBlUlXsoP11JeVEvFoVoq9pTR/9Aw/Hk1UanP6XQyaNAgAMaPH09+fj5PPvkkzz77bFSO31zQCPKbTx+mfNchrp15Cxf2uTDqNURbp3pNPfbYY2iaxj333NO07fzzz0fTtBZfP/zhDztbZ0QFK3zYM+PMLkMIIaImtH6P2VWcmM2mk9Ijjn6jMxh7UR/O++5QqoeXcTgQ5LyzxptSk2EY+Hy+qB9XKcXjX/2Osi2FXD3jpm4RTqATLSj5+fk8++yzjB59/BjrO+64g9/85jdN9+PirP3h7+yXhG9bGQGPHVcfmaBNCNH1KUPFzJTnEGpB2JdfiZERICfroogfb/bs2UyfPp0+ffpQVVXF3LlzWbx4MQsXLoz4sY/13Jq/c2DVds6/eAYX9Yv8z24VHQoo1dXV3HjjjTz33HM88sgjxz0eFxdHz549O11ctGiahjsvjUC5F+/2MtyDU80uSQghIkoZijUf72PHyiJ0m9bwpaPr2tH7+tHtNrvOyPN6k9LDnD845723kMSyLIbefPzloEgoKiripptu4uDBgyQnJzN69GgWLlzI1KlTo3L8Rm9sfYMNn69gxNlncG3etVE9ttk61MA3a9YsZsyYwUUXtZ7k/vWvf5GRkcHIkSOZPXs2tbW1nSoyWmzJLlTAMLsMIYSIuDNmDiB7UAoJqS7c8Y6midwC/iDeGj/VZT7Ki+oo2V/Nod0VrPusgB2riiJe1/od23j8j/9i1/6jU/OXV1Wy/2M/1bmFTInSMN/nn3+ePXv24PP5KCoq4uOPP456OPlkzyd89tF79D5tMD8Y94OoHtsK2t2C8uqrr7Jq1Sry8/Nbffw73/kOffv2JTs7m3Xr1nH//fezdetW3nrrrVaf7/P5WlzTq6ysbG9JYRMorsORZe3LUUIIEQ7jL+nXruc//cNPWfHOLkoPVAOhATaarpGWfeK5N9Kz4+k/JrPNxzhcWswHf11HQm0v5v92DWNv3M+UMyfxyj8/wBFI5YrvjW1XzbHsm0PfMO+Dl0nP683PzvpFTF2OC5d2BZSCggLuvvtuFi1ahNvtbvU5P/jB0ZQ3atQoevXqxZQpU9i5cycDBw487vlz5szh17/+dTvLjhBdk2nuhRCiFSPO7U354Rpqq/wAHNhahsNtY/+W0lafX1flx53g4PY2BhRvvZfn/7QQd30K4+5MZembh9j0kptNa16FdWnYTytnUJ++Yft5rGxr6Vaee+fPJPRO5aEpv8amd8+pLzSl2j6v+9tvv82VV16JzXb0ZAWDQTRNQ9d1fD5fi8cAampqSEhIYMGCBVx88cXH7bO1FpTc3FwqKipISopuh1Wj1k/9/mrcQ6QPihBCdMayt3ey45vDfO+Rs075XMMwePxP/8Szoxejbk7h/DMnUu/388zf38C+vge1rgp+OGcqiXFdd86PRvur9vObeQ/gjPfw2JV/iKl5TiorK0lOTg7b53e7WlCmTJnC+vXrW2y79dZbGTp0KPfff/9x4QRgzZo1APTq1frCRS6XC5fL1Z4yIkaPc6C5bQTKvdhTWm8hEkII0Qaq7aOEnpv7JvHbc0i7xMf5Z04EwOlwcPesb7Ng6eekpw3qFuHkSN0RHnnnQTSHjYe/9WhMhZNIaFdASUxMZOTIkS22xcfHk56ezsiRI9m5cydz587l0ksvJT09nXXr1nHvvfdy7rnntjoc2YqcuYl4t5VJQBFCiE5QBm2aqfbtTz6m/otUtDElfPuK6457/JJzz4lEeZZT46/h4f/8iqAvwIPXPUqGRyYODetMsk6nk48//pgnnniCmpoacnNzufrqq/nv//7vcB4msgxl2vTPQgjRVSilOFUDyoqNa9jzlp/6nDL+6wfXR6cwC/IH/Tz44QP4ymr4r2t/RW5irtklWUKnA8rixYubbufm5rJkyZLO7tJUvl0VOHt372Y1IYToLKXgZAll78H9LP37box4Pz++d2arXQS6A0MZ/L9PH6a2oIzvX/UThqYNNbsky7DwRMfR59tTgS3JiR4nKxkLIURnnKwFpbKmmrlPfo6GzrfvPYfE+BMPVe7KlFL8YdnjlG45wFUzvtdlVyXuKFkssBnNYUOzS2YTQojOUopWO8kGg0H++sR8PJWZTP5Rb/qcYABFdzBv6zwKvtnCudMuZWq/6E4CFwvk07gZR3Y8/kOxMeutEEJY2gkWI3z6H6+TUNCLAVe6mDhqVPTrsoiAEWDpso9IG5nDdUOP7xwsJKC0oLxB9AS5vCOEEJ3VWgvK3Hfex7a6B66zKvnW1AtMqswaPtn3Cd6aWr499kazS7EsCSjN6B47Rl3A7DKEECLmHdsH5bMVyylZ4MA76BC3f/cK0+qyio/y3yOldxZ5aXlml2JZElCa8e2RETxCCBEOzeco37x7J6v/r5ja9CPM+unV6Hr3/ujZULKBisNHmD7+crNLsbTu/VtyDKM2gC3RaXYZQggR85QKzSlVXHaEd59aRcBZz233TcPttMbM4WZ6Y+1ruBPiOD/nfLNLsTQJKA0MbwA9TgY1CSFEOCgFRtDg+T8txOHzMGPWaLLS0s0uy3RFtUUc3LKHMyae120XAWwr+UQGVFDh3VKKZ1TblwUXQghxYspQFO+rJl7LZPhNCYwYONjskizh9c2voes6Vwy+wuxSLE9aUADv9jI8IzLQbDLFvRBChMO+yn0ApE31MWXSJJOrsQZf0MemVasYMGYEic5Es8uxPGlBgdB4fYdkNSGECJeCrI1U6nX84aoYWostwj7Y9QEBn5/rR95gdikxQT6VAXuGh7oNJQRr/GaXIoQQXYKv9xGODNphdhmWoZRicf5CMvpn0yepj9nlxAQJKIAjKw738HQCxbXUbTyCv1hmkxVCiM5Szccad3NfH/qa2tIqZp52tdmlxAwJKA00XcPVLxnPiHTQNGrXFROsrje7LCGEEF3AO6vfxJOawOk9ZUHAtpKA0gpHhoe40Zn4D9fi21VudjlCCBFzWlsosLsqqCygZFch559+sZyXdpBOsifhHphCsKqe2nXFMspHCCHawVNex1mvruO9ty5F6RpoGkrX0XQdpWtoug7Nb9t0tGP+hwZas6tETZeMlAIUquH2muI15CbkkuFpbZ6VVt63tWNuNH9KiwChtXJTa3WXjQ+pVl5zuLaEjOx0Lu1/6QleKFojAeUUbIlOPMPTqVtfjDsvDd0jp0wIIU7lvD3xpK/0Uph7GE2BZig0pRq+A0qhGwoU6EZou2r8bG/MIVrjHY0WvVmOCQiTlAL2YdcKj+6j+dNP0hdGO0k3mZM/1rZ92oIwKHE4OVMTcNvdJ96hOI582raBZtfxjMnEt6sC5Q3izE3EliRT4gshxIkMqUuiqncOF320yOxSTHXklX9y5KUPOP/7/2N2KTFH+qC0kaZpuAem4BmRjv9QDcFKn9klCSGEZQVLSrD36BHVYz7zzDOMHj2apKQkkpKSmDRpEh9++GFUa2hOGQYVb39G3Jg+OHr2NK2OWCUBpQOcfRMJHPGaXYYQQliWCgTR7NFtpM/JyeGxxx5j5cqVfPPNN1x44YXMnDmTjRs3RrWORjVffkmgtIa0715ryvFjnQSUjggqgtX1eLeVofyGjPUXQohjKCOIZovuR8zll1/OpZdeyuDBgxkyZAiPPvooCQkJLF++PKp1NCr911s4eiXjOe00U44f66QPSgfocQ7iRmWiAgZ1m45AUOEalIItUfqlCCEEAEEDTFytNxgMMm/ePGpqaphkwlpA9Xv24N1ykKyfXCdDiztIAkonaHaduNGhFZBr1xXjGZaG5pDls4UQQhlBiHILCsD69euZNGkSXq+XhIQE5s+fz/Dhw6Nex5F/vYoe5yLpshlRP3ZXIQElTOwZHrzbykJj6PWjaVn32HHmJES9qVMIIUxlKDQt+u97eXl5rFmzhoqKCt544w1uvvlmlixZEtWQEqyuoWbpRhKnjUd3uaJ23K5GAkqYOLMTIDvhuO1GrR/v9nIIKrBpoTmAGpv7GvquKEPhGpCC7pLWFyFEFxEMQpQ7yQI4nU4GDRoEwPjx48nPz+fJJ5/k2WefjVoN5W+/jeEPkvad66N2zK5IAkqE6XEOPEPTTvocZSjq1hXjGZmBZpeWFiFE7FOGga6b/35mGAY+X/SmhVCGQcX8z4gblYujV6+oHbcrkoBiAZqu4RmRgXdbGZ7hrU3VLIQQMSYYBFt0W4Vnz57N9OnT6dOnD1VVVcydO5fFixezcOHCqNVQ89UyAkeq6fnLO6N2zK5KAopFaA69Rd8VIYSIZUoZaFF+TysqKuKmm27i4MGDJCcnM3r0aBYuXMjUqVOjVkPJsy+j4cUzYULUjtlVSUCxEN1tI1hVL8OVhRCxz4Rhxs8//3xUj9ea+t2HMbwVMrQ4DMy/QCiaOPsm4dtdQbDGb3YpQgjRKWZM1Ga2QGkp2Fyk336D2aV0Cd3rt8fiNE3DMyoD/4FqvDvKUYbMUCuEiFEmT9RmhrLX5qE5HKTeIKN3wkECisVomoZ7SCrO3gnUrSuW1hQhRGwyjG7Vr075/VR+sIz4MwdjT001u5wuQfqgWJTuseMZk4lvZwX1gVBnM3u6G1uaW65tCiEsTxkGWjdqQan6+GOCVXWkfe/bZpfSZUhAsTBN03APSgFCc6UEjtTh21ZG44UfDXANSAmNABJCCCsJmjPVvVlK//0erv5ZuPPyzC6ly5CAEiM0XcORGYcjM65pmwoa+HZWoAyF7rLh6J2A7uw+f7EIIayrO7Wg1G3YSP3eYnr+9x1ml9KlSECJYZpNxz0kdK3TqPXjP1BNsNqPo0ccjqy4U7xaCCEiyDCiPlGbWUr/79/YkuNJvOACs0vpUiSgdBF6nANX/2QA/IdqqNt0BM2p4+qfgmaTPitCiOhSRjDqE7WZIVBSQu03u0j99hQ0E9Ye6srkbHZBjp7xOHrGY9QH8W4vA8CW4MCZk2hyZUKIbqObDDMufe110DVSr7na7FK6nO7Tg6kb0p02PEPT8AxNQ/fY8W4rM7skIUQ30R0malP19VR9uIL4M/OwpaSYXU6XIy0o3YQ93QM2ndr1Jbj6JmFLkun0hRCRo+r91K3fQN2aNSjVMPawae7JxvvHfw9WVeHbuhX3yFHobhc0n1bhRLfRWr/Z7DlKqYbDqlD/GKVC2wwV2qYUyjBCz1EK1MmeE9qXd/MmgtVe0r4nM8dGggSUbsSe4sKe4qJ2fQmekekyn4oQImJsSUnUrljBnhu67rwgemIvPOPH4h4yxOxSuiQJKN2QMycB/4Fq6ZMihIiYvq+8TKCo6OiGxj+ITtEKonxe/IcO4ejdG83haNbqAsfcOdrycuztY+4rpUJ/kGka6HroWBpouh7a1vClNbvdlud5d1QSNza7nWdGtJUElG6ofn8VnhEZZpchhOjCbMnJ2JKTO/Ra97BhYa4m/IxaP/Z00LrJUGozdO0eTKJV9ow4vJuOYNTKOj9CCNERvr2VOPsmmV1GlyYBpRty9orHPSId3+5Ks0sRQoiYowx19FKPiBgJKN2Upmlg01B+w+xShBAipvh2V+DqL60nkSYBpbuzy18AQgjRHsoXRHdJF85Ik4DSjdmSnASK68wuQwghYob/cI2sdRYlElC6MWd2ggQUIYRoh8ARL/YMj9lldAsSULo5e5aHuo0lGL6A2aUIIYSlBWv86HFyaSda5Ex3c47MOOzpHnw7y1F+A/eQVDS75FYhhDhW/d5K3MPSzC6j25BPIoGma7gHp+LOS6VufQkqICN7hBCiuWB1PegytDiaJKCIJppNxzMqA9+uCuq2lOI/XGN2SUIIYQlVi/fj6t+xmXFFx8glHtGCZtdxD0kFwF9SR92GEjS3DXtmHPZkl8nVCSFE9KmgwjU4Bd0l09pHkwQUcUKODA+ODA8qYOAvrqN2dwWeMZnSxCmE6Fbq91bi6icTs0WbXOIRp6TZdZy94nH2T8ZfKJd9hBDdi1EvE7OZQQKKaDNbkhPlC1C3+Qj1+6vMLkcIIUQXJgFFtJmmabgGpOAZlg42Hf8haU0RQnRthjeA7pa+J2aQgCI6xNkrnmC1H++O8tDKnkII0QXV76/C2TvR7DK6pU4FlMceewxN07jnnnuOe0wpxfTp09E0jbfffrszhxEW5R6UgjMnAe+2MrzbylBKgooQomtRQYXmkL/lzdDhs56fn8+zzz7L6NGjW338iSeekNEe3YDutuMZmoYzJyE0yZu0pgghuhJ5SzNNhwJKdXU1N954I8899xypqanHPb5mzRr+8Ic/8MILL3S6QBEb9DgH7rxUvNvKqNtaSt3WUrxbS/FuK6P+QLW0rgghYo5RH5TWExN1aNzUrFmzmDFjBhdddBGPPPJIi8dqa2v5zne+w9NPP03Pnj1PuS+fz4fP52u6X1lZ2ZGShAXorlBrSnPKUBjV9Xg3l4IealGzp7mxZ3qkhU0IYWn+/dU4c6T/iVnaHVBeffVVVq1aRX5+fquP33vvvZx11lnMnDmzTfubM2cOv/71r9tbhogRmq5hS3LhGX50FtpAqZe69SW4BiRjS3CaWJ0QQpxYsLoel8wea5p2tV0VFBRw9913869//Qu3233c4++++y6ffvopTzzxRJv3OXv2bCoqKpq+CgoK2lOSiEH2NHdozZ/t5bIwoRDCkpRSaBJOTKWpdnQOePvtt7nyyiux2Y7+owWDQTRNQ9d1fvSjH/H000+j63qLx3Vd55xzzmHx4sWnPEZlZSXJyclUVFSQlCRTC3dlKmiEWlIGp2KLd5hdjhBCNPEX16LpGvZ0j9mlxIxwf363K6BUVVWxd+/eFttuvfVWhg4dyv33309GRgYlJSUtHh81ahRPPvkkl19+Of379z/lMSSgdC9KKXzby9ETHDizE8wuRwghAKjbWop7SKr0lWuHcH9+t6sPSmJiIiNHjmyxLT4+nvT09KbtrXWM7dOnT5vCieh+NE3DPSSV+oM1+PZV4uojoVQIYQEKCScmk/FTwhKcveIxqvzSJ0UIIQTQwWHGzZ2qX4nMfyHayj00jdp1xcSNyUTT5S8XIYQ5AhU+bEkywtBs0oIiLEOzaXhGpFO3voRAhe/ULxBCiAgIHKrB0TPe7DK6PQkowlJ0p424MZnU76uSafOFEKZQIK24FiABRViSq38Svp3lZpchhOiO5G8jS5CAIizJluDEnurGu63M7FKEEN1IsMaPHtfp7pkiDCSgCMuyZ3iw94jDt6vc7FKEEN2Ev7Ba5mSyCAkowtLsyS4Mvww9FkJEhwoqNLt8NFqB/CsIy9MdNoxav9llCCGEiCIJKMLynP2S8O2qMLsMIUQXZ9QH0RzysWgV8i8hLE/TNRw94yWkCCEiyr+/CmdOotlliAYSUERMsGd4MHwBs8sQQnRhRr2B7rKZXYZoIAFFxIRgZT22RJl6WgghugsJKCIm+A/X4OglU08LISJDBQ2ZPdZiJKCImKB8QTSb/LoKISIjUOrFnuExuwzRjLzjC8sLVtZjS3aZXYYQogsLlvmwpcj7jJVIQBGWFyj3Yk93m12GEKIrU0ou8ViMBBRheUZtAD3OYXYZQgghokgCirA++aNGCBFhsoCx9UhAEZZnS3DiL641uwwhRBcmfwdZjwQUYXnO3gkEjnjNLkMIIUQUSUARlheskknahBCRo4IKpIOs5UhAEZanOXUCR+pQSq4SCyHCz6jzo3vsZpchjiEBRVie7rLjHpxK3dpiVMAwuxwhRBdj1MlIQSuSgCJigu6x4xmViXdrqdmlCCG6mNBUBtKCYjUSUETs0AFNrhMLIcJL+YJosoqx5UhAETHDt7McV78ks8sQQnQ1SqHJHz+WIwFFxAzNaUMFpKOsEEJ0BxJQRMxw5ibi21mO4Q2YXYoQQogIk4AiYoamaXjGZuLbUW52KUIIISJMAoqIKZqmgUN+bYUQoquTd3oRewzphyKEEF2dBBQRU3z7KrGne8wuQwghRIRJQBExJVjuw54pAUUIIbo6CSgiprgGpuDddMTsMoQQQkSYBBQRU2zxDpy5SXhlJI8QIgxU0JCVjC1KAoqIObYkZ+hNRQghOkkWCrQuCSgiNslAHiFEGBi1AXSPLBRoRRJQRMwx6oMy1FgIERahFhQJKFYkAUXEHN+Octx5qWaXIYToAnS3DcMbNLsM0QoJKCLmuAamULfhCN4d5aiA9EURQnScPc1N4Eid2WWIVki7log5ustG3JhMlD+Ib1cFylDYEp04eyeYXZoQIsZoDhvIHzqWJAFFxCzNYcM9JHSpJ1Duo25jCbZkF86cRJMrE0II0VlyiUd0CfYUF54RGehxDrzbyswuRwghRCdJQBFdij3NjS3VhW9vpdmlCCGE6AQJKKLLcWTGARAo9ZpciRAiViglUxdYjQQU0SW5+ibh3VqK4QuYXYoQwuL0RCdGld/sMsQxJKCILitufA/q91WZXYYQwuLs6R4ZamxBElBEl2TUBfBuOoJrQLLZpQghLE532VD1Mlmb1cgwY9HlBI7U4S+qxTMmE00zf5XSem8dRbt3UldZSXpuX4yAH3diEvEpqZaoTwghrEgCiuhSfLsqQAfPsHSzS2HLl0v4+t03Kd6zq9XH3YlJpPbshSsunvScXEacP5XMPv2iW6QQQliUBBTRZXh3luPI9GBLcplWQ2VxEYd2bWfH18vY/MViBow/ndMuuZzMvv3xJCZRUXQIm8NBTVkZJfv3Un7oIL7aGla+/w7emhou+dE9ptUuRLcmrZmWIwFFdAmGL4DyG1EPJ5u/WMyWL5dgd7mpqyinYNN6AFJ69OLC237I2GkzWlzGScrMaro9+Iyzmm7/+8FfoAyZblsI0yiFUkouu1qIBBTRJfh2VeDOS4vqMXeuXMEHf3kcpyeOnoOGYHM4uOTH95I7YjRJGZnt2pemaSDzMAhhGj3egVEbwBbvMLsU0UACioh5/pI6dI8dTY/OXz5GMMii555mw2cf0WfUWGb89OfEJXVutJCmazJRlBAmsqe58ZfUSUCxEAkoIqbVbQgtEOjqF53hxHVVlXz9zhts+Owjpv7gJ4y6cFpYmoQ1JKAIYSY9zoGqk3mTrEQCiohZKqjQXDacuZFdvbiyuIity7/gSMFedq7Kx1tVyWmXzmT0lIvDdgxpQRFCiJYkoIiYpdk0iPBn+vb8Zbz3p9+i221k5PYlb9I5TLjsSlJ69AzzkaQPihBCNCcBRcS2CH2oF+/dzfK3XmP7iq/oPWw4V97/EE63JyLHAtB0XVpQhBCiGQkoImaF4wO9sqSI+tpaqkuPsP3rZRw5UEBdVSWlBwpI7tGTs799ExMuvxJdt4Wh4hOTUTxCCNGSBBQRu4IKbB3voLrukwUs+vtTTfdTe2WT0acfGX36cfrMaxhy5mQcLnc4Kj01TfqgCGE2zWPHqPWjx8lIHivoVEB57LHHmD17NnfffTdPPPEEAHfeeScff/wxhYWFJCQkcNZZZ/Hb3/6WoUOHhqNeIZpodj0UUtpJKcWOb5bz2cvPMfzcCxl90XQ0TaPX4DzTJmnSNA2lZKI2IcxkT/cQKPXilIBiCR0OKPn5+Tz77LOMHj26xfbx48dz44030qdPH0pLS3n44YeZNm0au3fvxmaLbDO5ECdTVVrC9hXL2JG/jIKN6+g/djwX3f5jHO4otZKcRCigmF2FEN2bHmfHv99vdhmiQYcCSnV1NTfeeCPPPfccjzzySIvHfvCDHzTd7tevH4888ghjxoxhz549DBw4sHPVCnEMpUAZ6qSTtCml2Ld+LQv++kdqKsrp0X8gV97/EP3HTbDOtNbSgiKE6SzzfiCADgaUWbNmMWPGDC666KLjAkpzNTU1vPjii/Tv35/c3NxWn+Pz+fD5fE33KysrO1KS6KacuYn49law5+A69qxZSTAQwBUXz5Azz8YwguS/+yaFWzcTqPeRM2wk3/nfP5KYlmF22cfRNB1lBM0uQwghLKPdAeXVV19l1apV5Ofnn/A5f/3rX/nFL35BTU0NeXl5LFq0CKfT2epz58yZw69//ev2liEEAEFbgIV/foIdhd+Q1X8g7vh49m9az9pFHwDgcLk544pr6Tk4jz4jR4d9NE5r/bA6QtPAkGs8QgjRpF0BpaCggLvvvptFixbhPsl1+xtvvJGpU6dy8OBBHn/8ca677jq+/PLLVl8ze/Zs7rvvvqb7lZWVJ2xtEeJY9XV11JaXM2bqDC76/o8ACAb8lB86hKZrxCWl4E5IiMixT9QPqyNkHhQhhGhJb8+TV65cSVFREaeddhp2ux273c6SJUv485//jN1uJxgMNVEnJyczePBgzj33XN544w22bNnC/PnzW92ny+UiKSmpxZcQbZWQmkbSiGzK1xU0bbPZHaTn5JKWnROxcNK8H1Zqamqn9xe6xCN9UIQwm+ayYfgCZpchaGdAmTJlCuvXr2fNmjVNXxMmTODGG29kzZo1rY7SUUqhlGrRz0SIcHIlxuN0uaJ6zOb9sMJB0zQJKEJYgD3dQ+CI1+wyBO28xJOYmMjIkSNbbIuPjyc9PZ2RI0eya9cuXnvtNaZNm0ZmZib79+/nsccew+PxcOmll4a1cCEaeVKSKa3ai1IqKr3w29IPq73kEo8Q1qAnOPAXVptdhiDMM8m63W4+//xznnjiCcrKyujRowfnnnsuX331FVlZWeE8lBBNEtMz8HvronKstvbDai+ZqE0Ia5ChxtbR6YCyePHiptvZ2dl88MEHnd2lEO3iTkjAqbv5z8OPMPzyaQyacEbEjtW8H1ajYDDI0qVLeeqpp/D5fB2akFAu8QghREuyFo+IeYPPmEygvp7ti75g1V/nse+stVxw+x0R+UuosR9Wc7feeitDhw7l/vvv7/BsyZpuw5CAIoQQTSSgiJinaRrDz72QYedcwNdvv8Hud7+i7NIDpGXnhP1Yp+qH1VGaroMhfVCEEKJRu0bxCGFlmqYxaOKZGCpI2cFCs8tpF13XpQVFCIvQHDpGvczsbDZpQRFdSmp2Ns74OPauXsXA8adH5ZjN+2F1lKbLPChCWIUt3UOw1IveM97sUro1aUERXYqu29B0G3u/WEnx3t1ml9Nmmq7JWjxCWIQt0Umwst7sMro9CSiiyxl946V4tAR2rQrfPCWRJvOgCGEdmq6FlkoXppKAIrqcwWdOJq53BqU7C079ZIuQPihCCNGSBBTRJaWNyKV6V1HMtEpouk36oAghRDMSUESX1GtIHvW1dZTs22N2KW0iM8kKIURLElBEl5SdNxylDBY/85zZpbSNpkFsNPYI0T3YdFRA/mgwkwQU0SV5EhJxpsVRU3iEle+/TV11ldklnZSs/iGEtdjT3ARKZVVjM0lAEV3WJQ/8DFd8HDveWMqC3z1O+eFDZpd0UkqaUISwDFuKi2C5z+wyujUJKKLLSsrM4rq//J7TfnwtvsJqPrj/f3n7f35NZXGR2aUdT1ZQFcJSZKix+SSgiC7NZrczeOIkLvvdA4y742rqK2tY8Mjj7PhmhfVGzciboegGli5dyuWXX052djaapvH222+bXZKwKJnqXnQLCWnpDJt8Hr3zhvHpE38l/+l/sy75XeL6ZqACQfpPPp2B40/H4XKbUl9oFI8phxYiqmpqahgzZgy33XYbV111ldnlCAuTgCK6laSMLK545GEKt21h48cf4ztYQTAYZNXf32SV9gbxGWnE9c8ga/BAeg4cTEafftjs0fjPRC7xiMhZV7yO17a+hoaGrulomobW7HdOa7jE2GJbw23tmMuPzbfrmt60z8b96jS73fB4i9f2gt7X9uYQoT5hC3Yv4NDaQyetp3FfNs2GhoZNb/iu2dC00PfGYzbf1vRYQ03NvzS00HloqLnxnDQ/P64Kg/6BONx2c/5w6e4koIhuKXvIULKHDG26X1q4n/2bNlC0fQc1u4+wMX87G9SH2Ow24rPSiOufSUa/vmT1H0Bm3wHYHY4IVCVNKCIyFu5ZyLs732Vs5lgMDJRSTZMYNnbObt5J+9gJDpue02x78/003UZhKANDhe4HVfC4fRz7a/5l4Zds3br1uGMfW09QBY9+RxE0ghgYTceLhLE1eYzXzuaeifdEZP/i5CSgCAGkZeeQlp0DF4Xu+31eivbs5vDObRRv203VloMc/mozG5VCt9mI75FGyvBcxl16OQlp6Z0+vqYd/6EgRDj1T+7P/136f2aX0YJ2vcb/m/z/uOKKKzq9L0MZLUNMw/fGANP41RiaWgSrZrcNDFCh/T27+ClKDh3sdG2iYySgCNEKh8tN77xh9M4bBpeGtgXq6ynet5uD27dStGUnB7/YSMGXa7n6D4/giuvksuwyikdEkIbW5QNw46WbcMro2ZMj2w6EdZ+i7SSgCNFGdqeTXoPy6DUoD6ZDRdEhFjzwe/Lnv8nZN97UqX1XFh2mqqQ4TJWK7uZQzSFe3/o6ARUARdOlFkWodWDl4ZVmlxiTeifnsL1mPYYywh5+xKlJQBGig5KzetLjnOEUfr4B49tBdN3W4X1t+vyzMFYmuptFexfx3PrnyE3MbdkBtKHTJ8A5OeeYXGXsyU3Mxa/8FNUW0TO+p9nldDsSUITohCGTzuLQ4g1s+GQRo6de0uH9jJl6KWsXfRDGykR3YiiDeEc8H1xl/d+h6upqduzY0XR/9+7drFmzhrS0NPr06WNiZcfLTcwFoKCqQAKKCaTNSohOyB4yjIyJg9j670/If+etDu/HnZBIUmZWGCsTwpq++eYbxo0bx7hx4wC47777GDduHA8++KDJlR2vd2JvdHT2V+03u5RuSQKKEJ005Uc/JuWMvux+7ytqyss6tA+lDGQuFNEZWoz8/px//vlNI2eaf7300ktml3Ycl81FiiuZgsoCs0vpliSgCNFJmqYx6dpvYzhh4eNPdGy0hFIykEd0WFcfoWMmd3ICR0osuH5XNyABRYgwSEhLZ+Jt1+HdX87hndvb/XoFaDJKQHRCrLSgxJq4rCR8R6rNLqNbkk6yQoRJ39Hj+Jp/8eajD3Lezd9vmkZb0zRovK3rgIamN0w1rmtomk75wUK5wiM6TKHk9ydCeqZms3rLbrPL6JYkoAgRJjVlpdQbPlL0TNa+9E67X5+dMwTvtnb0YVGqbRO8tfa8k722rfuNhMZj64RCnR4KcWgN67M03taPud3wmNbwulDwo+k5jQGxcb9N+2tF/YFqnL0Tovczh4MCf8DPvzb967g5UJrfbxx+3Lj2TPN1aU60nk7z9WmOXWfn2P2sOryKNHca/ZL7tSzv2Gn1TzLNfvOf6fhNx29sdVsrl7yOfV5bj1lUW0RNoJYKXwXJruTjnyAiRgKKEGGSnNWDm15+Bo7rAGg0bTvuMSO0hogyDFzxCRFa4ye2KCN0njBoOmcYrWw3Ql9KAcHQOTYMQtuVCk1Y1vg81fh6mh47/sChjYY3gFHjb7ENsPRsv8NK+zK2Jo/FSz5sCBWhS4ZNSwI2WxxQKQMFDVO6hz6mWws04qigw8Bv+M0uo9vRlMV6V1VWVpKcnExFRQVJSUlmlyOEEN2SUg0L/zWuUdO4COAxCwI2LtinlKK4rhiXzUWiMxFo24rITbdbuUZ1olautjyv1f218RjHPs+u23HanG2qpTsL9+e3tKAIIYQ4jqZp2DQbNto+Q3JmXGYEKxLdjQwbEEIIIYTlSEARQgghhOVIQBFCCCGE5UhAEUIIIYTlSEARQgghhOVIQBFCCCGE5UhAEUIIIYTlSEARQgghhOVIQBFCCCGE5UhAEUIIIYTlSEARQgghhOVIQBFCCCGE5UhAEUIIIYTlWG41Y6UUEFq2WQghhBCxofFzu/FzvLMsF1CqqqoAyM3NNbkSIYQQQrRXVVUVycnJnd6PpsIVdcLEMAwKCwtJTExE07R2vbayspLc3FwKCgpISkqKUIWxQ85HS3I+WpLz0ZKcj5bkfLQk56Ol1s6HUoqqqiqys7PR9c73ILFcC4qu6+Tk5HRqH0lJSfIL1Iycj5bkfLQk56MlOR8tyfloSc5HS8eej3C0nDSSTrJCCCGEsBwJKEIIIYSwnC4VUFwuFw899BAul8vsUixBzkdLcj5akvPRkpyPluR8tCTno6VonA/LdZIVQgghhOhSLShCCCGE6BokoAghhBDCciSgCCGEEMJyJKAIIYQQwnK6TEBZtWoVU6dOJSUlhfT0dH7wgx9QXV3d9PiRI0e45JJLyM7OxuVykZuby1133dVl1/w51flYu3Yt3/72t8nNzcXj8TBs2DCefPJJEyuOrFOdD4Cf/vSnjB8/HpfLxdixY80pNEracj727dvHjBkziIuLIysri5///OcEAgGTKo6sbdu2MXPmTDIyMkhKSuLss8/ms88+a/GcTz75hLPOOovExER69uzJ/fff363PR35+PlOmTCElJYXU1FQuvvhi1q5da1LFkXWq8/HSSy+haVqrX0VFRSZWHhlt+f2A0HkZPXo0brebrKwsZs2a1a7jdImAUlhYyEUXXcSgQYNYsWIFCxYsYOPGjdxyyy1Nz9F1nZkzZ/Luu++ybds2XnrpJT7++GN++MMfmld4hLTlfKxcuZKsrCz++c9/snHjRn71q18xe/ZsnnrqKfMKj5C2nI9Gt912G9dff330i4yitpyPYDDIjBkzqK+v56uvvuLll1/mpZde4sEHHzSv8Ai67LLLCAQCfPrpp6xcuZIxY8Zw2WWXcejQISAU6C+99FIuueQSVq9ezWuvvca7777LL3/5S5Mrj4xTnY/q6mouueQS+vTpw4oVK/jiiy9ITEzk4osvxu/3m1x9+J3qfFx//fUcPHiwxdfFF1/MeeedR1ZWlsnVh9+pzgfAH//4R371q1/xy1/+ko0bN/Lxxx9z8cUXt+9Aqgt49tlnVVZWlgoGg03b1q1bpwC1ffv2E77uySefVDk5OdEoMao6ej5+/OMfqwsuuCAaJUZVe8/HQw89pMaMGRPFCqOrLefjgw8+ULquq0OHDjU955lnnlFJSUnK5/NFveZIKi4uVoBaunRp07bKykoFqEWLFimllJo9e7aaMGFCi9e9++67yu12q8rKyqjWG2ltOR/5+fkKUPv27Wt6TlveY2JRW87HsYqKipTD4VCvvPJKtMqMmracj9LSUuXxeNTHH3/cqWN1iRYUn8+H0+lssTiRx+MB4Isvvmj1NYWFhbz11lucd955UakxmjpyPgAqKipIS0uLeH3R1tHz0VW15XwsW7aMUaNG0aNHj6bnXHzxxVRWVrJx48boFhxh6enp5OXl8corr1BTU0MgEODZZ58lKyuL8ePHA6Fz5na7W7zO4/Hg9XpZuXKlGWVHTFvOR15eHunp6Tz//PPU19dTV1fH888/z7Bhw+jXr5+5P0CYteV8HOuVV14hLi6Oa665JsrVRl5bzseiRYswDIMDBw4wbNgwcnJyuO666ygoKGjfwToVbyxiw4YNym63q9/97nfK5/Op0tJSdfXVVytA/e///m+L595www3K4/EoQF1++eWqrq7OpKojpz3no9GXX36p7Ha7WrhwYZSrjbz2no+u3oLSlvNxxx13qGnTprV4XU1NjQLUBx98YEbZEVVQUKDGjx+vNE1TNptN9erVS61atarp8YULFypd19XcuXNVIBBQ+/fvV+ecc44C1Ny5c02sPDJOdT6UUmr9+vVq4MCBStd1peu6ysvLU3v27DGp4shqy/lobtiwYepHP/pRFCuMrlOdjzlz5iiHw6Hy8vLUggUL1LJly9SUKVNUXl5eu1pgLd2C8stf/vKEHY8av7Zs2cKIESN4+eWX+cMf/kBcXBw9e/akf//+9OjR47gln//0pz+xatUq3nnnHXbu3Ml9991n0k/XfpE4HwAbNmxg5syZPPTQQ0ybNs2En6xjInU+YpWcj5baej6UUsyaNYusrCw+//xzvv76a6644gouv/xyDh48CMC0adP4/e9/zw9/+ENcLhdDhgzh0ksvBYiZcxbO81FXV8ftt9/O5MmTWb58OV9++SUjR45kxowZ1NXVmfyTtk04z0dzy5YtY/Pmzdx+++0m/FQdF87zYRgGfr+fP//5z1x88cWceeaZ/Pvf/2b79u2tdqY9EUtPdV9cXMyRI0dO+pwBAwbgdDqb7h8+fJj4+Hg0TSMpKYlXX32Va6+9ttXXfvHFF5xzzjkUFhbSq1evsNYeCZE4H5s2beKCCy7g+9//Po8++mjEao+ESP1+PPzww7z99tusWbMmEmVHTDjPx4MPPsi7777b4hzs3r2bAQMGsGrVKsaNGxepHyNs2no+Pv/8c6ZNm0ZZWVmLZeMHDx7M7bff3qIjrFKKgwcPkpqayp49exg+fDhff/01EydOjNjPES7hPB/PP/88DzzwAAcPHmwKaPX19aSmpvL8889zww03RPRnCYdI/H4A3H777axatYrVq1dHpO5ICef5ePHFF7ntttsoKCggJyen6Tk9evTgkUce4Y477mhTTfaO/SjRkZmZSWZmZrte03jN/IUXXsDtdjN16tQTPtcwDCB0fTkWhPt8bNy4kQsvvJCbb7455sIJRP73I9aE83xMmjSJRx99lKKioqZRCIsWLSIpKYnhw4eHt/AIaev5qK2tBY5vCdF1vek9opGmaWRnZwPw73//m9zcXE477bQwVRxZ4TwftbW16LqOpmktHtc07bhzZlWR+P2orq7m9ddfZ86cOeErNErCeT4mT54MwNatW5sCSmlpKSUlJfTt27ftRYX1wpSJ/vKXv6iVK1eqrVu3qqeeekp5PB715JNPNj3+/vvvqxdeeEGtX79e7d69W7333ntq2LBhavLkySZWHTmnOh/r169XmZmZ6rvf/a46ePBg01dRUZGJVUfOqc6HUkpt375drV69Wt15551qyJAhavXq1Wr16tVdbtSKUqc+H4FAQI0cOVJNmzZNrVmzRi1YsEBlZmaq2bNnm1h1ZBQXF6v09HR11VVXqTVr1qitW7eqn/3sZ8rhcKg1a9Y0Pe93v/udWrdundqwYYP6zW9+oxwOh5o/f755hUdIW87H5s2blcvlUj/60Y/Upk2b1IYNG9R3v/tdlZycrAoLC03+CcKrrb8fSin1j3/8Q7ndblVWVmZOsVHQ1vMxc+ZMNWLECPXll1+q9evXq8suu0wNHz5c1dfXt/lYXSagfO9731NpaWnK6XSq0aNHHze869NPP1WTJk1SycnJyu12q8GDB6v777+/y/4inep8PPTQQwo47qtv377mFBxhpzofSil13nnntXpOdu/eHf2CI6wt52PPnj1q+vTpyuPxqIyMDPVf//Vfyu/3m1Bt5OXn56tp06aptLQ0lZiYqM4888zjOgNfcMEFTe8fZ5xxRpfsLNyoLefjo48+UpMnT1bJyckqNTVVXXjhhWrZsmUmVRxZbTkfSik1adIk9Z3vfMeECqOrLeejoqJC3XbbbSolJUWlpaWpK6+8ssWw9LawdB8UIYQQQnRPsdH9XAghhBDdigQUIYQQQliOBBQhhBBCWI4EFCGEEEJYjgQUIYQQQliOBBQhhBBCWI4EFCGEEEJYjgQUIYQQQliOBBQhhBBCWI4EFCGEEEJYjgQUIYQQQliOBBQhhBBCWM7/B06FvsoiXy+EAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aDP = float(statePop)/nDistricts\n",
    "maxCCBratio = 1./4.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "maxCCBpop = maxCCBratio * aDP\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "nFuses = 0\n",
    "for c in set(has1neighborCs).difference(set(collapsedCountyList)):\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "    if countyPop[c] > maxCCBpop:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        nc = neighborCountyList[c][0]\n",
    "        plotPoly(countyGeom[nc],0.5)\n",
    "        plotPoly(MAP,0.2)\n",
    "        print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "        print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "        fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "        if fuseChoice == 0:\n",
    "            keepUnfused = True\n",
    "            break\n",
    "        elif int(fuseChoice) == 1:\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])  \n",
    "            hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "        elif int(fuseChoice) == 2:\n",
    "            CCBlist.append([c,nc ] )\n",
    "            CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "            hasFewNeighborCs.append(c)\n",
    "            passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "    else:\n",
    "        hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "        \n",
    "for c in set(hasFewNeighborCs).difference(set(collapsedCountyList)):\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "    if countyPop[c] < maxCCBpop :\n",
    "        CCBlist.append([c])\n",
    "        CCBpop.append(countyPop[c])\n",
    "        CCBno = CCBlist.index([c])\n",
    "    if c in passThruList:\n",
    "        CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "    if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "        CCBstarter = c\n",
    "        canAdd = True\n",
    "        while canAdd:\n",
    "            nbrSet = set()\n",
    "            for cc in CCBlist[CCBno]:\n",
    "                nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "            nPop = [countyPop[cc] for cc in nbrSet]\n",
    "            nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "            idx = np.argsort(nDist)\n",
    "            nbrList, newList = list(nbrSet), list()\n",
    "            for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                cc = nbrList[idx[i]]\n",
    "                if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                    newList.append(cc)\n",
    "                    CCBlist[CCBno].append(cc)\n",
    "                    CCBpop[CCBno] += countyPop[cc]\n",
    "                    #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "            if newList == list():  #no eligible neighbor counties found; stop\n",
    "                canAdd = False\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    plotPoly(countyGeom[cc])\n",
    "                    plotCenter(CCBno,countyGeom[cc])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "                    \n",
    "print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "plotPoly(MAP,0.15)\n",
    "for L in CCBlist:\n",
    "    print(CCBlist.index(L),\" \",L)\n",
    "    for c in L:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "            plotPoly(countyGeom[cc],0.4)\n",
    "            plotCenter(cc,countyGeom[cc],8)\n",
    "plt.show()\n",
    "rejectList = list()\n",
    "print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "print(\"You may suggest [ [18,20], [29], [15,1,3,6,65,57,25,50,63],[14,30, 37], [21] ] \")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "        print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "        isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "        if not (isOK == 1 or isOK == str(1)) :\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                rejectList.append(L)\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "                print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                CCBlist[i] = Lnew.copy()\n",
    "for L in rejectList:\n",
    "    del CCBpop[ CCBlist.index(L)]\n",
    "    del CCBlist[CCBlist.index(L)]\n",
    "stillAdding = True\n",
    "while stillAdding:\n",
    "    addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "    if int(addMore) != 1:\n",
    "        stillAdding = False\n",
    "    else:\n",
    "        isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "        if isOK == 0 or isOK == str(0) :\n",
    "            print(\"OK, we'll stop adding corner clusters\")\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            notGood = True\n",
    "            while notGood:       \n",
    "                Lnew = ast.literal_eval(isOK)        \n",
    "                if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                    notGood = False\n",
    "                    for L in CCBlist:\n",
    "                        if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                            notGood = True\n",
    "                            print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    if notGood == False:\n",
    "                        CCBlist.append(Lnew)\n",
    "                        CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                else:\n",
    "                    print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                    isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "206c9372-8ec8-4190-93ed-04df286466e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now identify the border counties + border fused units, and interior small counties with pop < 14734\n",
      "We defined a total of 4 unit (but not corner-cluster) counties in the map\n",
      "excluding the cut-out districts and collapsed counties\n"
     ]
    }
   ],
   "source": [
    "maxWholeBorderCountyPop = 0.02 * aDP   #to encourage contiguity, border counties > 0.02 aDP will be forced whole\n",
    "maxInteriorBorderCountyPop = 0.02 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "unitCounties, borderCounties = list(), list()\n",
    "origMAP = MAP\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    MAPexterior = MAP.exterior\n",
    "else:\n",
    "    maxArea = 0\n",
    "    for geo in MAP.geoms:\n",
    "        if geo.area > maxArea:\n",
    "            MAPexterior = geo.exterior\n",
    "            maxArea = geo.area\n",
    "            MAP0 = geo\n",
    "    MAP = MAP0\n",
    "for c in set(uncutCountyList).difference(set(collapsedCountyList)):\n",
    "    if countyGeom[c].intersects(MAPexterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                unitCounties.append(c)\n",
    "    else:\n",
    "        if countyPop[c] < maxInteriorBorderCountyPop and c not in allFusedCounties:\n",
    "            unitCounties.append(c)\n",
    "print(\"We defined a total of\",len(unitCounties),\"unit (but not corner-cluster) counties in the map\")\n",
    "print(\"excluding the cut-out districts and collapsed counties\")        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e0ff719c-59dc-4827-a522-11bd352f7524",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this state, do we have a lot of populated fragmented VTDs?\n",
      "591 fragmented VTDs out of 7059\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FYI, here are the locations of fragmented VTDs with pop > 3000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"For this state, do we have a lot of populated fragmented VTDs?\")\n",
    "nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "print(len(fragmentedVTDs),\"fragmented VTDs out of\",nVTDs)\n",
    "fragPop = [tractPop[v] for v in fragmentedVTDs]\n",
    "plt.hist(fragPop)\n",
    "plt.show()\n",
    "print(\"FYI, here are the locations of fragmented VTDs with pop > 3000\")\n",
    "for v in fragmentedVTDs:\n",
    "    if tractPop[v] > 3000:\n",
    "        plotPoly(vtdGeom[v])\n",
    "plotPoly(MAP,0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\n",
      "I split up 591 fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "looking for surrounds, now working on vtd 0\n",
      "looking for surrounds, now working on vtd 500\n",
      "looking for surrounds, now working on vtd 1000\n",
      "looking for surrounds, now working on vtd 1500\n",
      "looking for surrounds, now working on vtd 2000\n",
      "looking for surrounds, now working on vtd 2500\n",
      "looking for surrounds, now working on vtd 3000\n",
      "looking for surrounds, now working on vtd 3500\n",
      "looking for surrounds, now working on vtd 4002\n",
      "looking for surrounds, now working on vtd 4502\n",
      "looking for surrounds, now working on vtd 5002\n",
      "looking for surrounds, now working on vtd 5502\n",
      "looking for surrounds, now working on vtd 6002\n",
      "looking for surrounds, now working on vtd 6502\n",
      "looking for surrounds, now working on vtd 7002\n",
      "On loop 2 for county 24  we found that vtd frag 988 now has only 1 neighbor 7238\n",
      "special for WI , I believe that [1610, 1611] are surrounded by vtd (fragment) 2901 . Here, let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to apply the surrounding operation 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After surround checks, we appear to have 6841 building blocks defined. We captured 436 surrounded VTDs\n",
      "working on unit neighbor lists for county 0\n",
      "working on unit neighbor lists for county 20\n",
      "working on unit neighbor lists for county 40\n",
      "working on unit neighbor lists for county 60\n",
      "All done creating unit lists\n"
     ]
    }
   ],
   "source": [
    "#3/2/24 - split up all multipoly VTDs into fragments, divvy pop by area\n",
    "unitPop, unitCP, unitGeom, nbrUnitGeom, allUnits = list(), list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#These surrounded VTDs don't get transferred to the unit list\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(   countyGeom[c] )\n",
    "    nbrUnitGeom.append(countyGeom[c] )\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "\n",
    "nFragmentedVTDs,fragmentedVTDs, coastalFragmentedVTDs = 0, list(), list()  #a prev version treated coastal separately\n",
    "fragVTDgeom, parentVTDno, fragVTDpop = vtdGeom.to_list(), [v for v in range(nVTDs)], tractPop.to_list()  #these lists will expand to include vtd fragments \n",
    "origVTDgeom = vtdGeom.copy() #we create a parallel fragVTDgeom list which grabs the 1st fragment, then append fragments to the total list\n",
    "origVTDpop = tractPop.copy()\n",
    "VTDchildren = [[v] for v in range(nVTDs)]  #the list of all fragment numbers associated with the original VTD, including ones that get surrounded\n",
    "countyFragVTDset = [set(countyTractList[c]) for c in range(nCounties)]\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "            geos, areas = [geo for geo in vtdGeom[v].geoms ], [geo.area for geo in vtdGeom[v].geoms]\n",
    "            for i, geo in enumerate(geos):\n",
    "                if i == 0:\n",
    "                    fragVTDgeom[v] = geo\n",
    "                    fragVTDpop[v] = tractPop[v] * areas[i] / np.sum(areas)  #overwrite, then distribute balance below\n",
    "                else:\n",
    "                    fNo = len(fragVTDgeom)\n",
    "                    fragVTDgeom.append(geo)\n",
    "                    fragVTDpop.append( tractPop[v] * areas[i] / np.sum(areas) )\n",
    "                    parentVTDno.append(v)\n",
    "                    countyFragVTDset[c].add(fNo )\n",
    "                    VTDchildren[v].append(fNo)\n",
    "                    nVTDneighbors.append(0)\n",
    "                    lastVTDneighbor.append(-999)\n",
    "                    \n",
    "print(\"I split up\",nFragmentedVTDs,\"fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "\n",
    "debugV = -7616\n",
    "for kk,V in enumerate(populatedTractList):\n",
    "    if kk%500 == 0:\n",
    "        print(\"looking for surrounds, now working on vtd\",V)\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for v in VTDchildren[V]:\n",
    "            for vv in countyFragVTDset[c].difference({v}) :\n",
    "                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    lastVTDneighbor[v] = vv\n",
    "                    if v == debugV:\n",
    "                        print(\"I just added neighbor\",vv,\"to magicV\",v)\n",
    "                #if nVTDneighbors[v] >= 4:  #Enough to have >=2 even after surrounds.  Will do full neighbor list later\n",
    "                #    break\n",
    "            #if STATE == \"TN\":  #Tennessee has a lot of discontiguous county fragments.  Force the nearest intracounty to be a neighbor\n",
    "            #    if nVTDneighbors[v] == 0:\n",
    "            #        listMinusSelf = list( countyFragVTDset[c].difference({v}) )\n",
    "            #        fragDist = [fragVTDgeom[vvv].distance(fragVTDgeom[v]) for vvv in listMinusSelf ]\n",
    "            #        minIndex = fragDist.index(np.min(fragDist))\n",
    "            #        vv = listMinusSelf[minIndex]\n",
    "            #        nVTDneighbors[v] +=1\n",
    "            #        lastVTDneighbor[v] = vv\n",
    "            #        print(\"I am forcing an intracounty neighbor for VTDfrag\",v,\"of vtd\",V,\"in county\",c,\"to be VTDfrag\",vv)\n",
    "            #        forcedPairList.append([v,vv])\n",
    "            if nVTDneighbors[v] < 4:  #OK if a vtd has only 1 intracounty neighbor IF it touches another county, it's not surrounded\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if fragVTDgeom[v].intersects(countyGeom[cc]):\n",
    "                        if cc not in unitCounties + allFusedCounties:\n",
    "                            for vv in countyFragVTDset[cc] :\n",
    "                                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                                    nVTDneighbors[v] +=1\n",
    "                                    lastVTDneighbor[v] = vv\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                print(\"WARNING. vtd frag\",v,\"in county\",c,\"intersected county\",cc,\"but had no intracounty neighbors\")\n",
    "                                plotPoly(fragVTDgeom[v],2)\n",
    "                                plotCenter(\"iso\",fragVTDgeom[v])\n",
    "                                plotPoly(countyGeom[c])\n",
    "                                plotPoly(countyGeom[cc],0.2)\n",
    "                                plotCenter(cc, countyGeom[cc])\n",
    "                                plt.show()\n",
    "                        else:\n",
    "                            nVTDneighbors[v] +=1\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                if STATE == \"TN\":  #for TN, we tolerate some discontiguous counties\n",
    "                                    print(\"vtd fragment\",v,\"with no neighbors in its county\",countyNo[parentVTDno[v]],\n",
    "                                          \"borders a unit or fused county\",cc)\n",
    "                                else:\n",
    "                                    raise Exception(\"ERROR! Neighborless vtd fragment\",v,\"neighbors a unit or fused county\",cc)                                \n",
    "            if v == debugV:\n",
    "                print(v,\"has\",nVTDneighbors[v],\"neighbors.  its last is\",lastVTDneighbor[v])\n",
    "                \n",
    "for loop in range(3): #to catch surrounds of surrounds\n",
    "    for V in populatedTractList:\n",
    "        c = countyNo[V]\n",
    "        if c not in allFusedCounties and c not in unitCounties: \n",
    "            for v in VTDchildren[V]:\n",
    "                if nVTDneighbors[v] == 1:\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                        for sNo, s in enumerate(surroundedVTDs):\n",
    "                            if surrounders[sNo] == v:\n",
    "                                surrounders[sNo] = vv\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(vv)\n",
    "                    nVTDneighbors[vv] -=1\n",
    "                    nVTDneighbors[v] -=1 #in case this surrounder becomes a later surroundee\n",
    "                    fragVTDpop[vv] += fragVTDpop[v]\n",
    "                    fragVTDpop[v] = 0\n",
    "                    if lastVTDneighbor[vv] == v:  #find another neighbor in case this surrounder is also a surroundee in loop 2\n",
    "                        for vvv in countyFragVTDset[c]:\n",
    "                            if vvv not in [v,vv]:\n",
    "                                if fragVTDgeom[vvv].intersects(fragVTDgeom[vv]):\n",
    "                                    lastVTDneighbor[vv] = vvv\n",
    "                    if lastVTDneighbor[vv] == v:\n",
    "                        print(\"WARNING.  We did not find another neighbor of surrounder\",vv,\"other than surroundee\",v)\n",
    "                    if loop > 0:\n",
    "                        print(\"On loop\",loop+1,\"for county\",c,\" we found that vtd frag\",v,\"now has only 1 neighbor\",vv)\n",
    "if STATE == \"WI\":  #state-specific manual surround enforcement\n",
    "    specialSurrounded = [1610, 1611]\n",
    "    specialSurrounder = 2901\n",
    "    print(\"special for\",STATE,\", I believe that\", specialSurrounded,\"are surrounded by vtd (fragment)\",specialSurrounder,\". Here, let me show you\")\n",
    "    c = countyNo[parentVTDno[specialSurrounder]]\n",
    "    plotPoly(countyGeom[c], 0.5)\n",
    "    for v in specialSurrounded:\n",
    "        plotPoly(fragVTDgeom[v])\n",
    "        plotCenter(v,fragVTDgeom[v])\n",
    "    plotPoly(fragVTDgeom[specialSurrounder],0.2)\n",
    "    plotCenter(specialSurrounder, fragVTDgeom[specialSurrounder], 8)\n",
    "    plt.show()\n",
    "    shouldIcombine = int(input(\"enter 1 to apply the surrounding operation\"))\n",
    "    if shouldIcombine == 1:\n",
    "        for v in specialSurrounded:\n",
    "            vv = specialSurrounder\n",
    "            if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                for sNo, s in enumerate(surroundedVTDs):\n",
    "                    if surrounders[sNo] == v:\n",
    "                        surrounders[sNo] = vv\n",
    "            surroundedVTDs.append(v)\n",
    "            surrounders.append(vv)\n",
    "            nVTDneighbors[vv] -=1\n",
    "            nVTDneighbors[v] = 0 #we are capturing all surroundees (some of whom may touch other surroundees)\n",
    "            fragVTDpop[vv] += fragVTDpop[v]\n",
    "            fragVTDpop[v] = 0\n",
    "\n",
    "\n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] >1:\n",
    "                unitCP.append(fragVTDgeom[v].centroid)\n",
    "                unitGeom.append(fragVTDgeom[v])\n",
    "                unitPop.append(fragVTDpop[v])   #for now, ratio pop by area, not block decomposition\n",
    "                vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "                allUnits.append(v)\n",
    "#for V in populatedTractList:\n",
    "#    c = countyNo[V]\n",
    "#    if c not in allFusedCounties and c not in unitCounties:  \n",
    "#        for v in VTDchildren[V]: \n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] == 1:  #a surrounded VTD, transfer its pop to surrounder unit.  Don't bother with shifting centerpoints\n",
    "                print(\"somehow we missed 1-neighbor vtd frag\",v,\" with last vtd frag nbr\",lastVTDneighbor[v])\n",
    "            if nVTDneighbors[v] == 0 and v not in surroundedVTDs:\n",
    "                print(\"WARNING. unsurrounded vtd\",v,\"had no found neighbors\")\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(   CCBgeom[i])\n",
    "    nbrUnitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined. We captured\",len(surroundedVTDs),\"surrounded VTDs\")\n",
    "\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    for v in countyFragVTDset[c]:\n",
    "        if v in allUnits:\n",
    "            countyUnitList[c].append(allUnits.index(v))\n",
    "\n",
    "sketchyList = list()\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for uu in countyUnitList[cc] :\n",
    "                            if countyGeom[c].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu)\n",
    "                                unitNbrs[uu].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:  #non-unit county      \n",
    "            for u in countyUnitList[c] :\n",
    "                for uu in list( set(countyUnitList[c]).difference({u}) ) :\n",
    "                    if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                        unitNbrs[u].append(uu )  #will catch complement later in this county's loop\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if cc not in allFusedCounties and cc not in unitCounties: #see an above block for handling unitCounties\n",
    "                        for uu in countyUnitList[cc]:\n",
    "                            if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu )\n",
    "\n",
    "            for u in countyUnitList[c] :\n",
    "                for i,geo in enumerate(CCBgeom):\n",
    "                    if geo.intersects(unitGeom[u]):\n",
    "                        unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                        unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "                if len(unitNbrs[u]) == 0:\n",
    "                    print(\"ERROR - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has no neighbors\")\n",
    "                if len(unitNbrs[u]) == 1:  #after fragmentation, this unit appears surrounded.  Next block to confirm it has non-intracounty neighbors                       \n",
    "                    print(\"WARNING - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has only 1 neighbor=\",unitNbrs[u],\". Optional triage in next block\")\n",
    "                    sketchyList.append([u,unitNbrs[u][0] ] )\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            if STATE != \"WA\" or i * ii != 3 :  #In WA, we don't allow ferry connection of Island to Clallam+Jefferson\n",
    "                unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "                unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"All done creating unit lists\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "94741893-6835-45ac-9793-64cbaf4823b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Great! all units appear to have multiple neighbors; no checks needed.\n"
     ]
    }
   ],
   "source": [
    "if len(sketchyList) == 0:\n",
    "    print(\"Great! all units appear to have multiple neighbors; no checks needed.\")\n",
    "for L in sketchyList:  #hope that some of these flagged units picked up unit-county or CCB neighbors\n",
    "    print(\"sketchy unit\",L[0], \"has neighbor list\",unitNbrs[L[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cb4277b4-d6ef-4c8c-aa23-6fde227379ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8378940d-4387-4188-8ae1-a62010500ecb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now build the border topology\n",
      "counties and clusters done, now working on (frag) vtd-based units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now build the border topology\")\n",
    "borderUnits, borderType = list(), list()\n",
    "for c in borderCounties:\n",
    "    if c in unitCounties:\n",
    "        borderUnits.append(allUnits.index(c+0.5))\n",
    "        borderType.append(\"county\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if CCBgeom[i].intersects(MAPexterior):  #should usually be the case, but exception in VA\n",
    "        borderUnits.append(allUnits.index(i+0.25))\n",
    "        borderType.append(\"cluster\")\n",
    "print(\"counties and clusters done, now working on (frag) vtd-based units\")\n",
    "for c in borderCounties:\n",
    "    if c not in unitCounties + allFusedCounties:\n",
    "        for u in countyUnitList[c]:\n",
    "            if unitGeom[u].intersects(MAPexterior):\n",
    "                borderUnits.append(u)\n",
    "                borderType.append(\"vtd\")                \n",
    "if STATE == \"WA\":\n",
    "    print(\"adding a border unit between Island and Jefferson Counties, as these are only ferry-connected\")\n",
    "    borderUnits.append(2647)\n",
    "    borderType.append(\"vtd\")\n",
    "\n",
    "for i,b in enumerate(borderUnits):\n",
    "    plotPoly(unitGeom[b])\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(allUnits[b])\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "for c in unitCounties:\n",
    "    plotPoly(countyGeom[c],0.4)\n",
    "    plotCenter(\"unit\",countyGeom[c],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "937d923d-9e95-45e9-9aef-77cb4377781d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that the list of borderUnits is contiguous all around\n",
      "number of border units = 104\n"
     ]
    }
   ],
   "source": [
    "print(\"checking that the list of borderUnits is contiguous all around\")\n",
    "print(\"number of border units =\",len(borderUnits))\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        for uu in smallPieceList:\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "        print(\"above is with unit numbers; below is VTDfrag nos\")\n",
    "        for uu in smallPieceList:\n",
    "            vv = allUnits[uu]\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"v\"+str(vv),unitGeom[uu],8)\n",
    "        v = allUnits[u]\n",
    "        plotCenter(v,unitGeom[u],8)\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "20d57e82-0b63-4245-9f3e-37ca922ed5f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "in county 64 here are the fragVTDgeoms that intersect fragVTD 1611\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vB = 1611  #basis for the WI-specific intervention implemented above\n",
    "V = parentVTDno[vB]\n",
    "c = countyNo[V]\n",
    "for VV in countyTractList[c]:\n",
    "    for vv in VTDchildren[VV]:\n",
    "        if fragVTDgeom[vv].intersects(fragVTDgeom[vB]):\n",
    "            plotPoly(fragVTDgeom[vv])\n",
    "            plotCenter(vv,fragVTDgeom[vv])\n",
    "print(\"in county\",c,\"here are the fragVTDgeoms that intersect fragVTD\",vB)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "93603f77-77fa-4453-b54b-5ea07fcb6721",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n",
      "Bueno! no 'border units' that could be eliminated from the border set\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[allUnits[u]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b13c68e3-33ed-48b3-acca-78012ce0bf61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is the final border set\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "print(\"here is the final border set\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "173bb175-312b-4d08-a5b5-80a1d5d70416",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(isContiguous(borderUnits,unitNbrs)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fc1ae6e1-ef52-412b-a966-e9739071af8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For safekeeping, write the unit topology to a file\n"
     ]
    }
   ],
   "source": [
    "date_ = \"19May24\"\n",
    "print(\"For safekeeping, write the unit topology to a file\")  \n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        #for i,uu in enumerate(surrounders):  #no longer tracked\n",
    "         #   if u == uu:\n",
    "         #       unitVTDlist[u].append(surroundedVTDs[i])\n",
    "                \n",
    "unitNo = [u for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"neighborList\":unitNbrs, \"unitVTDlist\":unitVTDlist, \"unitParentVTDno\": unitParentVTDno, \"allUnits\":allUnits} )\n",
    "outname = STATE+\"unitTopologies_\"+date_+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d4baaea4-7af4-4407-aeb3-f4291d335f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()  #optional reset if we need to rerun the below clipPoly routine with alternate clipPolys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "abdd07e7-f9be-480a-9d3d-b3948eeaaa2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "toSquishCountiesList = list()   #default; if we did not have any clipPoly's to move in\n",
    "nClips = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4d5fdc3c-6126-4fa8-b484-1d0052c70aed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\n",
      "adding code here to 'push in' state panhandles ...\n",
      "performing squish no 1 for state WI\n",
      "clipPoly 0 intersects [1, 3, 25] counties and a total of 8 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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EhmGFiIgkioGFiIiIRI+BhYiIiESPgYWIiIhEj4GFiIiIRI+BhYiIiESPgUUqJNGvmIiIaHAMLERERCR6DCxEREQkegwsUiFz9ACIiIjsh4GFiIiIRI+BhYiIiESPgYWIiIhEj4GFiIiIRI+BRSrYh4WIiCSMgYWIiIhEj4GFiIiIRI+BhYiIiESPgUUq2DiOiIgkjIGFiIiIRI+BhYiIiESPgYWIiIhEz83RA5ioDF29OHKuAZeudMDT3RWa6ACoI/3h4uKgm0nYh4WIiCSMgcVK3X1GvPr5Ofz3lxfQ2WuEn9wNXX1G9BoFRAZ4YY1aCa1GhWSVAjIZ74QlIiKyBQYWKxi6evHAX/NRUNmMB2+Lw7q5kxAZ4IU+ownHLjVhT6EeHxy/jF2HzyMu1AdatQpZqSrEh/o6euhEREQTmkwQBElMJhgMBvj7+6OlpQUKhcLm+zeaBNz35rcovNyMv6y/FbMmBQ76vF6jCV+fa0COrhqfnqpBa3cfpisVyEpVQatRITLAy+ZjAwCUHQQSMuyzbyIiIjsZ6ec3r7CM0F++voCvyxvw7gNzhgwrAODu6oIliWFYkhiGrt4U/KukDjm6arycW4od+85i1qRAZGlUuH2GEqF+8nE8AiIioomLgWUEWjp68V8Hy3Dv3EmYPyVkxK/zdHfFqhQlVqUo0dbdh9zTNcjRVeO5PaexNecU5seHIEujwsqUCPh7udvxCIiIiCY2BpYR+J9jFeg2mvDzZQmj3oev3A1rZ0Zh7cwoNLX3YF9xDXJ0ejz9z0I8+3ExFieGQqtRIWNaGLw9RvHHwvt7iYhIwhhYRuCjk3qsmB5usymcQB8P3DMnBvfMiUGtoQt7CquRo9Pjsb+dhJe7K5ZPD4dWo8KiqSGQu7mObKeSuBOJiIhocAwsN1HX2oUz1Qb8f0vi7bL/cIUnHlgYiwcWxqLiSgdyCvXI0enx4FvHoPB0w+oUc5n0vPhguDqqxwsREZGDMbDcRGFlCwAMe6OtrcQEe2PD0inYsHQKSmtbkV2gR7ZOj/85VokQX3l/jxcl0mIC2eOFiIicCgPLTVy80g4vd1eo/D3H9X2nhvvhlysT8eSKqSi83IJsnR57CvX465GLiAzwglajglajxHRlf4M65hciIpIwBpabuNLegxA/D4dd0ZDJZNBEB0ATHYBf3z4N+RcbzVdd8ivw+hfliA/1QZYmEncFdELpkBESERHZHwPLTfT2meDhKo41Il1dZJgbF4y5ccHYmpWMr841IKdAjz8dLseJviJcyQtAlkaFNWoVVPZqUEdEROQADCw34enuis4eo6OHcQN3VxcsTQzD0sQwdPUaUfQvA96s9caLn5bid3vP4pbJ1xrUBfuyQR0REU1sDCw3EeonR31bN4wmQbRVOp7urrglNgi3LJ+F1q5e5J6uRbZOjy05p7El5zTmxwdbGtQpPNmgjoiIJh4GlpuID/VFr1HAhYZ2TAkT8SKG/X1Y/Dzd8f20KHw/LQqN7T3YV1yN7AI9fvWPQvz7R8VYkhiKrFQV0pPC4eUxwh4vREREDsbAchPqaH+4ushw9MIVcQeWQQT5eGDdnElYN2cSalq6sKe/x8uj752Et4e5QV2WRoXbEkLh4SaO+3SIiIgGw8ByEwpPd9wyORB7i6qxbs4kRw9naDeZrYrw98S/3RaHf7stDhcb2pGjM/d4+d8CPfy93LE6JQJZGhXmxLFBHRERiQ8Dywj8n1nR+OUHOpTVtiIh3M/RwxmcFa35J4f44OfpCfh5egLO1hiQXaBHTqEe7+dXItRPjswZSmSlqjAzOoAN6oiISBTGNA+wY8cOyGQybNy4ccD2vLw8LFu2DD4+PlAoFFi0aBE6OzuH3I/RaMRvfvMbxMbGwsvLC/Hx8XjuuecgCOJYICdLo0JkgBd27DsrmjHZSlKEAr9alYTDTy3FR4/Mxxq1EnuLqvH9147gthcO4ff7z+JMtUFyx01ERBPLqK+w5OfnY9euXVCr1QO25+XlYdWqVdi0aRNeeeUVuLm5QafTwcVl6Gz0+9//Hn/84x+xe/duJCcn49ixY1i/fj38/f3x2GOPjXaINuPh5oLfaqfj4beP452jFbh3rginhsZ4IUQmk2FmTCBmxgTi2czpOHrhCnJ0erx3tAJ//Fc5EsJ8odWokKVRYXKIj23GTERENEIyYRT/dG5ra0NaWhpee+01bNu2Dampqdi5cycAYO7cuVi+fDmee+65Ee9vzZo1CA8PxxtvvGHZduedd8LLywvvvPPOiPZhMBjg7++PlpYWKBQKq45npLZkn8JbeRfx3PdScM+tMeKaLjl3EJiSYfPd9vSZ8NW5emQX6PHp6Vp09BihjvJHlkaFTLUSSn82qCMiotEb6ef3qKaENmzYgMzMTGRkDPyArKurw9GjRxEWFob58+cjPDwcixcvxldffTXs/ubPn4/PPvsMpaWlAACdToevvvoKq1evHs3w7OY3a6bjx3Mn4d8/Ksa9b3yLg6dr0dNncvSw7MrDzQXLksKx80czcfzZ5fh/96RB6e+JFw6UYP6Oz3HXrjy8880lXGnrdvRQiYhIwqyeEnr//fdx4sQJ5Ofn3/C98+fPAwC2bNmCF198EampqXjrrbeQnp6O4uJiJCQkDLrPZ555BgaDAUlJSXB1dYXRaMTzzz+PdevWDTmO7u5udHdf+5A0GAzWHorVXF1k+I87UrBwSgh2HizDv711zKkqbLw8XJGpViJTrYShqxefnjI3qNucfQqbs09h4ZQQZGlUWJEcDj82qCMiIhuyKrBUVlbi8ccfR25uLjw9b1y92GQyX214+OGHsX79egDAzJkz8dlnn+HNN9/E9u3bB93v3//+d7z77rt47733kJycjIKCAmzcuBEqlQr33XffoK/Zvn07tm7das3wbWZFcgRWJEc4dYWNwtMd/2dWFP7PrChcaevG3uIa5BTo8eQHOnh85IJliWHISlVhWVIYPN3ZoI6clMkI9LQDghEwmfr/awSE7/y/WF39HfbdOwcG237977ur2wf7HegqB/wjbTdGchpW3cPy8ccfY+3atXB1vfYBZDQaIZPJ4OLigpKSEkyZMgVvv/02fvzjH1ue88Mf/hBubm549913B91vdHQ0nnnmGWzYsMGybdu2bXjnnXdw9uzZQV8z2BWW6Ohou97DMhRBEFBQ2YxsnR6fFFajrrUbUYFelptUkyL87B9e7HQPi7X0zZ34pLAa2To9iqpa4OPhihXJ5itQCxNC4C6ShSSJxkVNEdDZDLh7ATIXwMXV/F+Za///u5o/1Ef6YX89Qbj5c0ZqpO9pC77hgAdv3KdrRnoPi1VXWNLT01FUVDRg2/r165GUlISnn34acXFxUKlUKCkpGfCc0tLSYe9H6ejouKGKyNXV1XLFZjByuRxyuTgW9btZhc2UMF9kOUmFjSrACw8uisODi+Jwvr4Ne/rDy0cnqxDg7Y7VKUpkaVS4NTZI0tNnRACAlipg6srxCQJEEmdVYPHz80NKSsqAbT4+PggODrZsf+qpp7B582ZoNBqkpqZi9+7dOHv2LD788EPLa9LT07F27Vo8+uijAACtVovnn38eMTExSE5OxsmTJ/HSSy/h/vvvH+vxjTtXFxnmx4dgfnwItmalWCpsXv+iHC/llkId5Q+tWoU1GulX2MSF+uKx9AT8fNkUnKluRU7/0gB/+7YC4Qo5MmeokJWqgibKX9LTZ+SkOhoBr0CGFSIbsXmn240bN6KrqwtPPPEEGhsbodFokJubi/j4eMtzysvL0dDQYPn6lVdewW9+8xs88sgjqKurg0qlwsMPP4zf/va3th7euLpaYbMsKRydPUZ8frYO2boq/OenJfjdvjO4ZXIQtBoVbk+JQLCvOK4W2YNMJsN0lQLTVQr8amUiTlQ0W5YGePPrC4gJ8oZWo0SWJhKJESLtJExkrdYawC/C0aMgkoxR9WERo/How2Ir11fYfH3OHNwWTgmBVqPCytFW2IjkHhZrGE0Cvjlvnj7bV1yDls5eJIb7QatRQqtRYVKwtKfPSOJKDwAJK3iFhegmRvr5zcDiYNdX2Hx7sdF8VSYxDFqNCunTrKiwmYCB5Xo9fSYcLq1HTqEeuf0N6jTRAdCqzeElXHFjVRqRaHU0AlfKgehbHD0SItFjYJmAhqqw0WqUuC0hdPgKmwkeWK7X0dOHz87UIUenx79K6tFrMmFO7NXpMyUCfTwcPUSi4dWeAuR+QECMo0dCJHoMLBPc9RU25+raLBU2Wo0Sc2IHaVAnocByvZbOXhw4VYOc/ukzF5kMtyWYp89WJEfAV84Fx0mEOB1ENGIMLBIhCMKACpvLTZ0I85NjjVoFrUaJ1KsN6iQaWK7X0NaNvUXVyC7Q49ilJsjdXJA+LQxatQpL2aCOxKL9CtB4ntNBRCPEwCJBgiBYKmz2FFajoa3bUmHzo6AyRN+idfQQx01Vcyf29FcandIb4Ct3w4rkcGg1KiycwgZ15ECcDiKyCgOLxH23wkbTfQw1oQuQpVE5XYVNeX2bpUz6fH07gnw8sDolAlqNCrdODoILG9TReOJ0EJFVGFicSE+fCcWH/4nddfHXKmyi/KHVqLBGrUKEv3NU2AiCgNPVBmTr9Nijq0ZVcyciFJ5Yozav7zQjkg3qyM7aG4CmS0DULEePhGjCYGBxNiX7gZAEdPYacaT8Cj4/W4ej5xvRZzJBHRWA9GlhWDI1DP5e37lJdbA1TKwxWAAYaj8yl+88ZP2LwAn9C8AJ174ebnwjCB0mE3CqugWfnanFoZJ6NHX0IirAE8umhSM9OQqx4YGAqzvg6mFejM3Flf8iprHjdBCR1RhYnE1zJWDqHbCptasPh8vq8fnZOhy/2AQXmQyzJgciY1oYFiaEwsfjOzepjsePgmAa+LgaXiC7FmJsHBz6jObFKQ+eqcWXZXXo7u7G1GA5liYEYFG8P8K9XQBT3/WDvHEnJhPgGwqoZtp0bCQxnA4ishoDCw0wWIXNsqQwZGmcq8Kmu8+Iw6UNyNbpcfB0LTp7jUiNDkCWRoU1aiXChmpQd6XcHLBCEsZ3wDRxtNUBLZVAJKeDiKzBwEJDGrTCZno4tKnOVWHT0dOH3NO1yNFV44vSOvSZBMyNDUZWqgqrUyIQ4H1dg7rzXwBRtwAe3o4bMIlb7SlArgACoh09EqIJhYGFRuS7FTaB3u5YPUOJLCersGnp6MX+U9XI0VXjSLm5Qd2iqaHI0qiwfFoofCoOAVNXOnqYJGYl+80/I5wOIrIKAwtZZbgKG61GBXWU81TY1LV2YW9hNXIKq3H8UhOmutfhtlh/3HLrfCxJDHWa6TOyQmsNYNADkWmOHgnRhMPAQqNmMgk4WdmE7AI9PimqRkNbDyYHe0Pb3+Nlarifo4c4biobO1B46AO8XhmDopoO+MndsLK/x8uC+GC4Ocn0Gd1ETTHg6c/pIKJRYGAhm+gzmvDN+UZk66qwr7gGrV19SIrwM4cXtQoxwRK/p6O1FmiuAKJvwbm6VmTrqpGj0+NCQzuCfTxw+wzzFajZkwKdZvqMBsHqIKJRY2Ahmxt1hc1Edv4Lcymz57WfKUEQcEpvnj7L0elR3dIFlb8n1vSHuJRIhdNMnxEAQzXQVguoUh09EqIJiYGF7Gq4CptVyREI9PG4+U7Err3BXM4cM2fIp5hMAo5XmKfP9hZV40p7D2JDfKDVqJClUWJKmPNMnzktTgcRjQkDC42b4SpsMqaHw1fudvOdiNHFr4GwaYB30Iie3mc04Uj5FWTr9DhQXIPW7j5MUyosV6CigyQ+feasWB1ENCYMLOQQ362w8XR3QXqSeRXlCVVh03LZXPURfeuoXt7Va8QXpfXI1unx2ZladPWakBZjnj67Xa1EmJ8Ep8+cUWstYKhidRDRGDCwkMNVNnZgT6H5JtXT1Qb4yd2wIjkCWakir7DpbgMqvwFiF5vXGxqj9u4+HDxTi+wCPQ6X1cNoEjAvPhhZGhVWJSvh7z329yAH4XQQ0ZgxsJCofLfCJsjHA7fPiECWJlJ8FTYXvza34PcNs/mumzt6sL+4Btk6PfLOX4GbiwyLp4ZCq1Fh+fRweHtM0OkzZ1V6gA0FicaIgYVEabAKG6W/uUFdlibS8RU2Br256iPK/uvB1Bm68ElRNbJ1epysaIaXuyvSp5nXd1qcGAq52wSZPnNWbfXmkvdx+FkhkjIGFhK9ISts1EpkpaocU2FTfgiInjPuawZVNnYgp1CP7AI9zta0ws/TDav6p8/mxYl4+syZ1RQBngGcDiIaIwYWmlCGqrDRapTQqlXjU2Fj7AUuHAampNv/vYZRVttqWd/p4pUOhPiaG9RlaVRIixHZ9Jkz43QQkU0wsNCENVSFjVajQqY9K2yaLgF9XUBoon32byVBEFBU1YIcnR45umrUGLoQGeBlWd8pWcUGdQ7T0QhcOTfqKjIiuoaBhSRhqAobrVqF1Sk2rrC5Um7+b3C87fZ5MyYT0Nturkzq7TD38pC5AIGTv/M0AfkXG5GtM0+fNXX0Ii7UB1q1ClmpKsSH+o7fmMk8HeQVCPhHOXokRBMeAwtJznAVNhnTwuEz1gZ1IwksgmC+CtPdBvS0AYJp6Ocae4GedvPzTL3A1b9pVy+KCDAHFA8fQO4HuHmav248D0zJGHK3vUYTvj5nXiLh01O1aOvuQ7JKYVmcMjLAy5qjptEo2Q8krnL0KIgkgYGFJM0uFTYN54CG0v7eK9+ZapHhWuBw9wQ8fM1BQ9Z/M6xMZg4zV/8fAFzczc/x8AXcrFiqoOwgkDB0YLleV68R/yqp658+q0N3nwmzJwVCq1Hh9hlKhPrJR/6+NDKdzUDdGWDSPEePhEgSGFjIadiswsZkMl8JcfVwbJt1KwLL9dq6+5B7ugbZBXp8WdYAkyBgwZQQaDUqrEyOgL8XG9TZRHWhebkGTgcR2QQDCzklSVTYjDKwXK+pvQf7imuQravC0QuNcHdxweJE8/pO6dPC2KBuLDgdRGRTDCzk1CZ0hY0NAsv1ag1d2FNonj7TVTbD28MVGdPCkaVRYdHUUHi4scfLiHUZgJpCYPJCR4+ESDIYWIj6TbgKGxsHlutVXLk2fVZS2wqFpxtWp5gb9c2NC4brRLgC5Ui1p8w3SAfEOHokRJLBwEI0iMEqbKYrFchKFVGFjR0Dy/VKaq5Nn1U0diDEV265ApUWEyDeK1COVHoASFjh2HuciCSGgYXoJgarsJk1KRBZjq6wGafAcpUgCNBdNk+f7SnUo9bQjcgAL2g1KmRpVJim9GN4Acwl6lXHgdhFjh4JkaQwsBBZYbAKm/nxIcjSqLAyZZwrbMY5sFzPaBLw7YVG5BTqsa9/+iw+1AdZmkhkpaoQG+LjkHGJQt0Zc6+coFhHj4RIUhhYiEZpqAobc4O6caiwOXdw2MZx46XXaMJXZQ3I0elx4FQN2nuMSIlUIEujwhq1CioxTJ+Np5L95rWDeLWJyKYYWIhs4LsVNl7urlg+PRxajQqLpoaMrkHdzZz7zOELMH5XV68Rn5+tQ45Oj8/O1qGnz4RbJwdBq1Hi9hlKBPtKvEFdbxdQcQSIX+bokRBJDgMLkY0NVWGj1agwL96GFTYiDCzXa+3qxaenapFTaJ4+A2BuUKdWYmVKBBSeEmxQV18KuLiO7zpTRE6CgYXIjoausFEiLSZwbDepijywXK+xvQd7i6qRo9Pj24uNcHd1wdL+6bP0pHB4edjhCpQjlH5q/jNxkcjxEIkIAwvROBiuwkarUWK6chQN6iZQYLledUsnPik0hxfd5Rb4eFybPrstYQI3qOvrAS4eFsV9RURSxMBCNM6Gq7DRapSIG2mDugkaWK53saHdcgWqrK4NAd7uWJ0SAa1ahTkTrUFdwznzf0OmOHYcRBLFwELkQGOqsJFAYLlKEASU1LYiu0CPnEI9Khs7EeYnR2Z/g7qZ0ROgQd25g0Ds4v5VvInI1hhYiERisAqbWyZfa1B3Q4WNhALL9QRBQEFlM7J1euwprEZ9azeig7ygVZu7DCdFiLBBnbEPOH8ISFju6JEQSRYDC5EIDVZhMz8+2NKgTuHpLtnAcj2jScDRC1eQo9Njb1ENWjp7kRDmiyyNObxMFkuDuivlgMkIhE519EiIJIuBhUjkbqiwcXHBksRQ3K+8AM3i70unwuYmevpM+OpcPbIL9Pj0dC06eoxQR/lbps8i/D0dN7jyz4FJCwA3ifeZIXKgkX5+j+m2/R07dkAmk2Hjxo0Dtufl5WHZsmXw8fGBQqHAokWL0NnZOeR+Jk+eDJlMdsNjw4YNYxkekagF+Xjgx3Mn4X8enocjzyzDr1YlotbQhf86dAErt32Ax98/ic/O1KKnz+ToodqVh5sLliWFY+ePZuL4s8vx/+5Jg9LfEy8cKMG8HZ/hrl15eOebS2hs7xnfgZlMgLGXYYVIJEZ9hSU/Px933XUXFAoFli5dip07dwIwh5VVq1Zh06ZN0Gq1cHNzg06nwx133AG5fPC/+PX19TAajZavi4uLsXz5chw6dAhLliwZ0Xh4hYWk4mJdC3RffIz3L/kir8ET/l7mCpsszQSssBkDQ//0WbZOj6/PmafPFk4xr++0IjkcfvZuUHelHDD1AaGJ9n0fIidn1ymhtrY2pKWl4bXXXsO2bduQmppqCSxz587F8uXL8dxzz4168Bs3bsSePXtQVlY24pvwGFhIUkwmCOcP4bwpHP8472apsAn1kyNzhhJZqROkwsZGGtq6sa+4BjkF5ukzDzcXLEsMQ1aqCsuSwuDpbofps/NfAFGzAQ+R3E9DJFF2DSz33XcfgoKC8PLLL2PJkiWWwFJXV4fw8HD84Q9/wN/+9jeUl5cjKSkJzz//PBYuXDiifff09EClUuEXv/gFfv3rXw/5vO7ubnR3d1u+NhgMiI6OZmAh6RAE4MJhQBEJITj+hgqbqEBzg7ossVbY2Im+uRN7CvXI0VWjqMrcoG5FsvkK1MKEELi72qBBnSAApQeAxFVj3xcRDWukgcXqZWfff/99nDhxAvn5+Td87/z58wCALVu24MUXX0RqaireeustpKeno7i4GAkJCTfd/8cff4zm5mb89Kc/HfZ527dvx9atW60dPtHEIZMBsYuAyqOQGXswM2Y6ZsYE4tnM6ZYKm/eOVuCP/ypHQpivJbyIpsLGTlQBXnhoUTweWhSP8/VtyNFVI1tXhY9OVvU3qFMiS6PCrbFBo58+a7oIBE625bCJaIysusJSWVmJ2bNnIzc3F2q1GgAGXGE5cuQIFixYgE2bNuF3v/ud5XVqtRqZmZnYvn37Td9j5cqV8PDwQE5OzrDP4xUWcipVxwGZK6BKHbB5uAqbTLUSSv9hGtRJiCAIOFPdimydHjk6PaqaOxGukCNzhgpZqSpoovytuwJ18SsgQg148ncJkb3ZZUro448/xtq1a+Hqem2+2Gg0QiaTwcXFBSUlJZgyZQrefvtt/PjHP7Y854c//CHc3Nzw7rvvDrv/S5cuIS4uDv/85z9xxx13jHRYAHgPCzmBmiKgtxOIvnXQb3f2mBvUZeuqcKikHr1GE26ZHIQsjQqrUyJubFAnUYIg4ERFc//6TtVoaOvGpGBvS4O6xAi/m+2A00FE48gugaW1tRWXLl0asG39+vVISkrC008/jeTkZERFReH+++8fcNPtzJkzsXr16gFXXQazZcsW7Nq1C5WVlXBzs262ioGFnEJ9CdBeb+4NMswVA4dX2IiE0STgm/NXkF2gx77iahi6+pAY7oesVBW0ahVigr1vfFHTJaCnHQifPv4DJnJC49Y47vopIQDYuXMnNm/ejDfeeAOpqanYvXs3XnzxRRQXFyM+Ph4AkJ6ejrVr1+LRRx+17MdkMiE2NhZ33303duzYYfU4GFjIaVwpB1ouA5NvA1xufoOpQypsRKinz4TDpfXI1umRe7oWnb1GaKID+hvUKRGu6G9QdykPCEsCvAIdO2AiJ2G3m25vZuPGjejq6sITTzyBxsZGaDQa5ObmWsIKAJSXl6OhoWHA6w4ePIiKigrcf//9th4SkbQEx5sX4rvwBTB54U0X5QvxlePeuZNw79xJAypsHnn3hH0qbETKw80FGdPDkTE9HB09ffjsTB2ydXr8ft9ZbPvkNObEBplX1vZuhN8khhUisWFrfqKJyqA3TxHFzAPcrW9ff32FTXl9u+0qbCaYls5eHDhVgxydHsfPVSHNpRzuUxYjK1WF5dMj4Cu3+b/riOg6XEuIyBm01gB1Z4CoWwC576h2YfMKmwms8dJpfFFWj3fL3HHsUhPkbi5InxaGLI0KSxKdZ/qMaDwxsBA5i7Z6oLYYiEwDPP3HtKvBKmxigryh1SiRpYm8eYXNRHf+X0D0XMDdE5ebOvBJYTWydXqc0hvgK3fDiuRwZGlUWDBF2tNnROOJgYXImbRfAWoKAaUG8A6yyS6HqrDRapTQalSYFCyxBnUmI3D+EDAl44Zvlde3IUenR7ZOj/P17Qjy8bCs73TL5CC4OMn0GZE9MLAQOZvOJqBaB4QlA76hNt31UBU2WrU5vFgqbCayK+XmHiwhU4Z8iiAIOKU3IKdQjz26alQ1dyJC4Yk1avP6TjMinWf6jMhWGFiInFF3K1B1wrzCsF+EXd7i+gqbL0rq0WsyYU5sELQaFW5PUSLQx8Mu72t3l/LMvVdGOK1mMgk4UdGEHJ0enxRVo6GtB5ODvS1LJCSES3z6jMhGGFiInFVPB3A531z+7B9l17e6vsLm63MNcJHJcFtCCLQaFVYkT6AKG0EAyj4Fpq4c1cv7jCbknTev77SvuAatXX1IivCzhJfooEEa1BERAAYWRw+HyLH6uoGKb4CAGCAodlzesr61G/uKq5FdoB9QYaNVq7BU7A3qmiuBbgMQnjzmXXX3GfFFiXn67OCZWnT1mjAzJgBatblBXZgUps+IbIiBhcjZmYzApa8BPyUQcvOV0m1pqAobrUaFhWKssKk6DvhHA75hNt1te3cfDp6pRY5Ojy9K62E0CZgbFwxt//pOAd4TdPqMyIYYWIjIPNVReRTw8AUiUhwyhKEqbLQaFW4VS4VN6YFRTweNVEtHL/afMoe4vPIrcHWRYVFCKLQaFZZPD4fPRJk+I7IxBhYiuqbqhDm8RKYNu2iiPYm2wqatHmiuAKJmjdtb1rV2YW//FagTFc3wdHdB+rRwaNUqLEkMFff0GZGNMbAQ0UC1p4GuZnMrfweX3oqqwqam2FwZFBA9fu95ncrGDuzpDy9nqg3wk7thZX+Pl/nxwXAT2/QZkY0xsBDRja6u9DxpAeAqjikIh1fYlH4KJCx3eIgDgHN1rcjWVSNHp8eFhnYE+3jg9hnmK1CzYgLFMX1GZGMMLEQ0uKZLQNMFSwt6MRmswiY1OgBZGjtV2HS3AjVFwKT5tt3vGF2dPru6vlN1SxdU/p5Y0x/iklUKNqgjyWBgIaKhtVQBV8qAyNmjXjTR3r5bYdNnEjA3NhhZqTassKkvAVzdgaC4se/LTkwmAccrmpBdoMfeompcae9BXIiPJbxMCRPnnx/RSDGwENHwWmuButOAaibgFeDo0QzruxU2LjIZFk0NRdZYK2zKDgLxSwGXiXGTa5/RhK/LzdNnB4pr0Nrdh2lKBbI0Kmg1SkQFskEdTTwMLER0c+1XgNoiIHwG4BPs6NGMyKAVNknmHi9WVdgYe4GLXwLxy+w7YDvp6jXiXyX1yCnU47P+6bO0GPP0WaZahVA/uaOHSDQiDCxENDKdzYD+JBA2HfALd/RorDJUhY1Wo8KCm1XYNJwz32gbHD9+A7aTtu4+HDx9bfrMJAiYFx+MLI0Kq5KV8Pd2d/QQiYbEwEJEI9fdZl5/KDQRUKgcPZpRGarCRqtRYfakQSpszv9LlDcej1VzRw/2FZvXd8o7fwVuLjIsnnqtQZ23hziqw4iuYmAhIuv0dgEVeeYrDgExjh7NqA1XYaNVq5ASqYAMAMpygakrHD1cu6ozdGFPYTVyCvU4WdEML3dXZEwPh1atxOLEUMjdJsa9OyRtDCxEZD1jr3n9ocDJ5scEN1iFTWyID9YlClieoMCkpPHrbutolY0dlhB3tqYVCk83rOqfPpsXxwZ15DgMLEQ0OiYjcPErwD9KEvd3XHV9hU198SGc6I5ElDLC0uPF7g3qRKSsthXZ/es7XbrSgRBfD2T2T5+lsUEdjTMGFiIaPZPJfKXFNxwInero0dhcz+l9+Nw0c9AKm9vVSoT5Seu+lqEIgoCiqhZkF+ixp7AaNYYuRAZ4YY1GCa2aDepofDCwENHYCIL5nhavQCBsmqNHYzuGaqCtFlClAmCFzVUmk4D8i43I1pmnz5o6ehEX6tPf40WF+FA2qCP7YGAhorETBHP1kLsXEDHD0aOxjarjgH8M4Bt6w7dYYWPWazTh63MNyNbp8empWrR19yFZZW5Qt0ajQmSAl6OHSBLCwEJEtlN1HJC5mLviTnSln46oOmiwCpv0aWHI0qicqsLG3KCuDtk6PT47U4fuPhNmTwrsXyJByQZ1NGYMLERkW9U6oK8HiJotipWNR6WzCagvBWLmWPWy71bY+Hm6YVVyBLJSnavCprWrFwfP1CK7QI8vyxpgEgQsmBICrUaFlckR8Pdyjukzsi0GFiKyvdrTQLcBiJ4zMUNLTbF53ST/qFHvYrAKm9tnKJHlZBU2je092F9cg2xdFY5eaIS7iwsWJ5rXd8qYFg4vD+e4AkVjx8BCRPZRXwq01wEx8wGXCXZlofRTIGG5TcLWkBU2anN5sDNV2NS0dOGTIvMSCbrKZnh7uCJjWjiyNCosmhoKD7cJ9nNC44qBhYjs50o5YKgCJi2YMCsdo7cLqPwGiFti810PVWGjVauQlepcFTaXrrSb13cq0KOk1tygbnWKElmpKsyNC4ark1yBopFjYCEi+2q8ADRXmEOL6wSonqkvNY8zKM6ubzNUhY22vzzYmSpsSmpaka2rQo6uGhWNHQjxlVuuQKXFBDjNFSgaHgMLEdlfc4U5uMTMA9w8HD2a4ZXlAvHp4zqNNVSFjVajwu0znKfCRhAE6C5fnT7To661G5EBXtBqVMjSqDBN6cfw4sQYWIhofLRcBq6cE/fKxyYTcO6gQxc7ZIWNmdEk4NsL5umzfcXVaO7oxZQwX8v0WWyIj6OHSOOMgYWIxo9BDzSUAlG3Ah4iXJOn8Txg7BPNMgPDVdikTwtzqgZ1X5VdnT6rQXuPETMi/aHVKLFGrYLKiabPnBkDCxGNr9YaoP4sED4D8Al29GgGKj8ETJoPuIlvCoYVNmZdvUZ8frYO2QV6fF5Sh54+E26dHARtqgq3p0Qg2Fd8f3ZkGwwsRDT+2uqB+jOAIlJcKz2XHgCmrnT0KG6KFTZmrV29+PRULbJ1enx1rgEAsGBKCLI0KqxIDofC0zmmz5wFAwsROYbJZG7lDwCRsxzfq6XlMtDZDESkOHYcVmKFjVljew/29l+Byr/YCHdXFyxNDEWWJhLLksLYoE4CGFiIyLGulJvDgmom4OnAv5OXjgDhKY4dwxiwwuaa6pZOfFJoDi+Fl1vg4+GK5dPDkZWqwsIpzjN9JjUMLETkeK215imi0CTAL8IxYxjhYocTwWAVNvGhPsjSRDpdhc2Fhnbs6V8ioayuDQHe7lidEgGtRoU5sc4zfSYFDCxEJA7dbeYpIkUkEDJlfN+7pQrobAQiZozv+46DwSpsUiIVyNKonKrCRhAEnK1pRU5/eLnc1IkwPzky1eb1nVKjnWf6bKJiYCEi8TCZAP1JwNRnXu15vNr5Xz4GBE4GfELG5/0cZMgKG40St89QOk2FjSAIOFnZjBydeX2n+tZuRAd5WXq8JEXws0GMGFiISHwaz5u746pmAp7+9n+/CVIdZEtDVdho1UqsTIlwmgobo0nA0fNXkFOox96iGrR09mJquLlBnVajwmQnmj4TOwYWIhKntjqg7jQQkggolPZ7H4MeaG8AlGr7vYfIDVVho9WokJ4U7jQVNj19JnxZVo8cnR6fnq5FR48Rmih/aPunzyL8Rdqh2UkwsBCRePW0m6dr/JT26z5bmW/uBeMdZJ/9TzBDVdhoNSrcluA8FTadPUZ8drYWOTo9Dp2tR6/p6vSZeX2nIB+Rr4klQQwsRCRuggDoTwDGXiBytu1XfHbC6aCRGrLCRq3CHCdqUGfo6sWB4hrkFFbj63MNkAFYmBACrdrcoM7PSabPHI2BhYgmhsYLQPMlQJkKeAXYZp+GaqCtFlCl2mZ/EjVchY1Wo8JMJ6qwaWjrxj7L9FkT5G4uWJYUBq1GhWVJYfB0d47pM0cY6ef3mK4B7tixAzKZDBs3bhywPS8vD8uWLYOPjw8UCgUWLVqEzs7OYfdVVVWFH//4xwgODoaXlxdmzJiBY8eOjWV4RDQRBMUCYclAdYG5DNkWWiqBgBjb7EvCZDIZpikV+NWqJHz5q6X45yPzkalWYk9hNb7/2hEs+s9DeGH/WZypNkAi/7YdUoivHPfOm4wPfjYfR55ZhidXTEVlUwceefcEZm87iF/8TwEOna1Dr9Hk6KE6rVFfg83Pz8euXbugVg+8oS0vLw+rVq3Cpk2b8Morr8DNzQ06nQ4uw7TnbmpqwoIFC7B06VLs27cPoaGhKCsrQ2Bg4GiHR0QTiW8o4HGreYqoswkITwbG8i/7zibeu2IlmUyGtJhApMUE4tnM6ZYKm3ePVuC1f5UjIcwXWRrnqLBRBXjhoUXxeGhRPM7XtyFHV41sXRX+ebIKgd7uWD1DaZ4+iw2Ci5NMn4nBqKaE2trakJaWhtdeew3btm1Damoqdu7cCQCYO3culi9fjueee27E+3vmmWfw9ddf48svv7R2KBacEiKSAEEwVxB1NptLnz28rd9Ha435wekgmxiswkYd5W9pUOcsFTaCIOBMdSuydXrk6PSoau5EuEKONWrzEgnqKH+nmT6zNbvew3LfffchKCgIL7/8MpYsWWIJLHV1dQgPD8cf/vAH/O1vf0N5eTmSkpLw/PPPY+HChUPub/r06Vi5ciUuX76ML774ApGRkXjkkUfw4IMPDvma7u5udHd3Dzjg6OhoBhYiKWipAq6UAWHTAd8w615b8Q0QMpVXWOxgsAqbWyYHIcvJKmwEQcCJimsN6hraujEp2NvSoG5quJ+jhzih2C2wvP/++3j++eeRn58PT0/PAYHlm2++wbx58xAUFIQXX3wRqampeOutt/Daa6+huLgYCQkJg+7T09Oc0H/xi1/gBz/4AfLz8/H444/j9ddfx3333Tfoa7Zs2YKtW7fesJ2BhUgiugzm7rjWtvQv2Q8krrLfuAjAjRU2ALBwSgiyNM5VYdNnNOHohUZkF5jXdzJ09SEx3A9ZqSpo1SrEBI/iKqGTsUtgqaysxOzZs5Gbm2u5d+X6wHLkyBEsWLAAmzZtwu9+9zvL69RqNTIzM7F9+/ZB9+vh4YHZs2fjyJEjlm2PPfYY8vPzkZeXN+hreIWFyAmYTED1yf7S51mA600+BFtrgNZq83QSjZvvVth4uLlgWWIYslKdq8Kmu8+IL0vN6zvlnq5FZ68RmuiA/ukzJcIVzjF9Zq2RBharbro9fvw46urqkJaWZtlmNBpx+PBhvPrqqygpKQFgnuK53rRp01BRUTHkfpVK5aCv+cc//jHka+RyOeRy51gfg8hpubiYg0rTReDSEfMihsNN9TRdBEITx2t01O9qhc298yZD39yJPYXmMulH3j0BHw9XrEiOQJZGhYUJIXB3lW6DOrmbKzKmhyNjejg6evrw2Zk6ZOv0+P2+s9j2yWnMiQ1CliYSq1MiEOgk02e2ZFVgSU9PR1FR0YBt69evR1JSEp5++mnExcVBpVJZgstVpaWlWL169ZD7XbBgwaCvmTRpkjXDIyKpCpwMyBVATSEQGAsEDvG7oasF8GJ1oSMNVWHz0cmq/gZ15lWUb40NknSDOm8PN2j7q6paOq9On+nx7MdF+O3/FuO2hBBkpaqwfHoEfOU2bpooUWNuHHf9lBAA7Ny5E5s3b8Ybb7yB1NRU7N69Gy+++CKKi4sRHx8PwBx81q5di0cffRSAuUR6/vz52Lp1K+666y58++23ePDBB/GnP/0J69atG9E4WCVE5AT6esylz64egFIzcNXn1lrAUAVEpg39enKIoSpsMmeYb1LVOFGFTX1rN/YWVSNHp8exS+YGdenTwpClUWFJovNMn13PLlNCI7Fx40Z0dXXhiSeeQGNjIzQaDXJzcy1hBQDKy8vR0NBg+fqWW27BRx99hE2bNuE//uM/EBsbi507d444rBCRk3DzAGLmAlfKgYtfDqwiajwPhE1z7PhoUDKZDNNVCkxXKfD0qkRLhU22To83v75gqbDRalRIjJB2hU2onxz3zZ+M++ZPxuWmDsv6Tj975wR85W5YkRyOLI0KC6ZIe/psNNian4gmps4moPYU4OlvDi5luawOmmBYYXNNeX2bJcSdr29HkI8Hbp9hXt/plsnSblDHtYSISPoEAbhyDmi6ZL53JWqWo0dEo8QKGzNBEHBKb0BOoR57dNWoau6E0t8Ta/rXd5oRKb3pMwYWInIenc2Amyfg7hwfalJ3fYXNFyXmBnXOWGFjMgk4UdGEHJ0enxRVo6GtB5ODvS1LJCRIpEEdAwsREU1411fYfH2uAS4ymVNW2PQZTcg7fwU5Oj32FdegtasPSRHXps+igybu9BkDCxERSQorbMy6+4z4oqQe2To9Dp6pRVevCTNjzNNnmTOUCJtg02cMLEREJFmXmzqwp9AcXk7pDU5bYdPe3YeDZ8zrO31RWg+jScDcuGBkaVRYlRKBAG/xT58xsBARkVM4V2eusMnR6XG+wVxhszrF3F1X6hU212vp6MX+U+Yy6bzyK3B1kWFRQiiyUlXImBYOH5FOnzGwEBGRU7FU2PSHF31LFyIU5gqbrFRpVtgMpa61C3v7e7ycqGiGp7sL0qeF90+fhULuJp7pMwYWIiJyWlcrbLJ1euy9rsJGq1EhS0IVNiNR2WiePsvW6XGm2gA/Tzes7F/faX58MNwcPH3GwEJERIRrFTbZBXrsP3WtwuZqeJnIFTbWOlfXimyd+d6fCw3tCPbxwO0zzFegZsUEOmT6jIGFiIjoO4aqsNGqzQ3qJlqFzWhdnT67ur5TdUsXVP6eUEcFYGlSKO6aHT1u02cMLERERMMYqsJGq1Fh9QSpsLEFk0nA8YomZBfo8fY3lwAAtyWEYPv3ZyAq0P5XnxhYiIiIRqi5owcHTtXcUGGj1aiwfLp4K2xsravXiDe+uoD3jlago6cPbz8wBymR/nZ9TwYWIiKiURiqwkarNlfYOEODuqb2Htz3l29R3dKFPT9faNe1nBhYiIiIxuiGChu5G1amiKfCxp4a2rpx+399CXWUP/77vlvs9j4MLERERDYkxgobe9tbVI1H3j2B/3loLubEBdvlPRhYiIiI7EAQBBRXGZBTOLDCZk1/mXSySiGZBnWCIGDVzi8xKdgbf/rJbLu8x0g/v53jLiIiIiIbkclkmBHljxlR/nhmVRKOXWpCjk6Pfxy/jD8dPo+4EB9LeJkS5uvo4Y6JTCbDD2+Jxu/2noGhqxcKT3fHjYVXWIiIiMauz2jC1+XmBnWfnqpBa3cfpikVyNKooNUox6VE2B4qGztw2wuH8OefzMby6eE23z+vsBAREY0jN1cXLJ4aisVTQ9HVm4J/ldQjR6fHzoOl+P3+s0iLCUCWRoVMtQqhfnJHD3fEogK9EOIrR9HlZrsElpFiYCEiIrIxT3dXrEqJwKqUCLR19+Hg6Vpk6/TY9skZ/Mee05gXH4wsjQqrkpXw93bcNMtIyGQyxIX64FJjh0PHwcBCRERkR75yN3xvZiS+NzMSzR092Fdcg+wCPZ75ZxGe/bgYi6dea1Dn7SHOj+VgHw80tvc4dAziPDNEREQSFODtgbtvjcHdt8agztBl6fHy+PsF8HJ3Rcb0cGjVSixODIXcTTwN6txcXdBndOwtrwwsREREDhCm8MT9C2Nx/8JYVDZ2WBYifOhtPRSebliVEgGtRoV5cY5vUNfZ0wdvD8cGKAYWIiIiB4sO8saGpVOwYekUlNa2IkenR7ZOj78fu4wQXw9kzlBCq1EhzUEN6qpbuqCOChj3970eAwsREZGITA33w5MrEvGL5VNRVNWC7AI99hRWY3feJUQGeGGNRgmtevwa1PUaTSira8OdaVF2f6/hMLAQERGJkEwmgzoqAOqoAPz69mn49mIjcnR6/D2/Eru+OI+4UJ/+Hi8qxIfar0HdyYpm9PSZkDYp0G7vMRIMLERERCLn4iLD3LhgzI0LxpasZHx1rgE5Oj3++8sL2HmwDMkqc4O6NRoVIgO8bPrenxTqEeYnx4xIf5vu11oMLERERBOIu6sLliaGYWliGLp6jTh0tg45hXq8lFuK7fvOYvakQGSlqrA6RTnmBnUtHb34x4kq/GTeJLg6eHFHtuYnIiKSgNauXuSerkWOTo8vyxpgEgQsmBICrUaFlckR8PeyvkHdluxT+PuxSvzrqSUI8/O0w6i5WrOjh0NEROQwje092FdcjRydHkcvNMLdxQWLE0ORpVEhY1o4vEZQonzwdC0efPsYfr16Gh5cFGe3sTKwEBEREWpaurCnUI+cwmroKpvh7eGKjGnhyNKosGhqKDzcbuzxkqPT48kPdFiaGIo/rptl11JqBhYiIiIa4NKVdkuPl9LaNig83bA6RYkliaEI9ZOjorEDH52swpdlDdBqVHjxB2q7d9xlYCEiIqIhldS0IltXhU8Kq3HxyrWFDTVR/nh4cTxWp0SMS58XBhYiIiIakbrWLrR09CLUT44Ab49xfe+Rfn6zrJmIiMjJhfl52q0KyFYcu5oSERER0QgwsBAREZHoMbAQERGR6DGwEBERkegxsBAREZHoMbAQERGR6DGwEBERkegxsBAREZHoMbAQERGR6DGwEBERkeiNKbDs2LEDMpkMGzduHLA9Ly8Py5Ytg4+PDxQKBRYtWoTOzs4h97NlyxbIZLIBj6SkpLEMjYiIiCRk1GsJ5efnY9euXVCr1QO25+XlYdWqVdi0aRNeeeUVuLm5QafTwcVl+GyUnJyMgwcPXhuYG5c5IiIiIrNRpYK2tjasW7cOf/7zn7Ft27YB33viiSfw2GOP4ZlnnrFsS0xMvPlA3NwQERExmuEQERGRxI0qsGzYsAGZmZnIyMgYEFjq6upw9OhRrFu3DvPnz0d5eTmSkpLw/PPPY+HChcPus6ysDCqVCp6enpg3bx62b9+OmJiYIZ/f3d2N7u5uy9ctLS0AzMtUExER0cRw9XNbEIThnyhY6W9/+5uQkpIidHZ2CoIgCIsXLxYef/xxQRAEIS8vTwAgBAUFCW+++aZw4sQJYePGjYKHh4dQWlo65D737t0r/P3vfxd0Op2wf/9+Yd68eUJMTIxgMBiGfM3mzZsFAHzwwQcffPDBhwQelZWVw+YPmXDTSHNNZWUlZs+ejdzcXMu9K0uWLEFqaip27tyJI0eOYMGCBdi0aRN+97vfWV6nVquRmZmJ7du3j+h9mpubMWnSJLz00kt44IEHBn3Od6+wmEwmNDY2Ijg4GDKZbMBzDQYDoqOjUVlZCYVCMdLDdVo8X9bjObMOz5f1eM6sw/NlHUeeL0EQ0NraCpVKNez9rlZNCR0/fhx1dXVIS0uzbDMajTh8+DBeffVVlJSUAACmT58+4HXTpk1DRUXFiN8nICAAU6dOxblz54Z8jlwuh1wuv+F1w1EoFPzBtQLPl/V4zqzD82U9njPr8HxZx1Hny9/f/6bPsaqsOT09HUVFRSgoKLA8Zs+ejXXr1qGgoABxcXFQqVSW4HJVaWkpJk2aNOL3aWtrQ3l5OZRKpTXDIyIiIomy6gqLn58fUlJSBmzz8fFBcHCwZftTTz2FzZs3Q6PRIDU1Fbt378bZs2fx4YcfWl6Tnp6OtWvX4tFHHwUA/PKXv4RWq8WkSZOg1+uxefNmuLq64u677x7r8REREZEE2LzZycaNG9HV1YUnnngCjY2N0Gg0yM3NRXx8vOU55eXlaGhosHx9+fJl3H333bhy5QpCQ0OxcOFCfPPNNwgNDbXJmORyOTZv3nzDFBINjufLejxn1uH5sh7PmXV4vqwzEc6XVTfdEhERETkC1xIiIiIi0WNgISIiItFjYCEiIiLRY2AhIiIi0ZNEYDlx4gSWL1+OgIAABAcH46GHHkJbW9uA5zz22GOYNWsW5HI5UlNTb7rPxsZG/PznP0diYiK8vLwQExODxx57zLJm0URmj/MFAF1dXdiwYQOCg4Ph6+uLO++8E7W1tXY4gvE3knNWUVGBzMxMeHt7IywsDE899RT6+vqG3W9paSnuuOMOhISEQKFQYOHChTh06JA9D2Vc2Ot8AcAnn3yCOXPmwMvLC4GBgfje975np6MYX/Y8Z4C5O3hqaipkMhkKCgrscATjyx7n6+LFi3jggQcQGxsLLy8vxMfHY/Pmzejp6bH34YwLe/2MNTY2Yt26dVAoFAgICMADDzxww35tYcIHFr1ej4yMDEyZMgVHjx7F/v37cerUKfz0pz+94bn3338/fvjDH454v3q9Hi+++CKKi4vx17/+Ffv37x9yqYCJwl7nCzCv1J2Tk4MPPvgAX3zxBfR6Pb7//e/bcPSOMZJzZjQakZmZiZ6eHhw5cgS7d+/GX//6V/z2t78ddt9r1qxBX18fPv/8cxw/fhwajQZr1qxBTU2NnY/Kfux5vv7xj3/g3nvvxfr166HT6fD111/jnnvusfMR2Z89z9lVv/rVr6BSqex0BOPLXufr7NmzMJlM2LVrF06dOoWXX34Zr7/+On7961+Pw1HZlz1/xtatW4dTp04hNzcXe/bsweHDh/HQQw/Z/iCsWvlQhHbt2iWEhYUJRqPRsq2wsFAAIJSVld3w/M2bNwsajWZU7/X3v/9d8PDwEHp7e0c7XIez1/lqbm4W3N3dhQ8++MCy7cyZMwIAIS8vzyZjd5SRnLO9e/cKLi4uQk1NjeU5f/zjHwWFQiF0d3cPut/6+noBgHD48GHLNoPBIAAQcnNz7XQ09mev89Xb2ytERkYK//3f/23fA3AAe52zq/bu3SskJSUJp06dEgAIJ0+etMtxjBd7n6/rvfDCC0JsbKztBu8g9jpnp0+fFgAI+fn5lm379u0TZDKZUFVVZdNjmPBXWLq7u+Hh4TFgwSQvLy8AwFdffWXT92ppaYFCoYCbm8377Y0be52v48ePo7e3FxkZGZZtSUlJiImJQV5e3ugHLAIjOWd5eXmYMWMGwsPDLc9ZuXIlDAYDTp06Neh+g4ODkZiYiLfeegvt7e3o6+vDrl27EBYWhlmzZtnxiOzLXufrxIkTqKqqgouLC2bOnAmlUonVq1ejuLjYjkczPux1zgCgtrYWDz74IN5++214e3vb6QjGlz3P13e1tLQgKCjIRiN3HHuds7y8PAQEBGD27NmWbRkZGXBxccHRo0dtegwTPrAsW7YMNTU1+M///E/09PSgqakJzzzzDACgurraZu/T0NCA5557zj6XucaRvc5XTU0NPDw8bliAMjw8fEJPbwAjO2c1NTUD/pIDsHw91PHLZDIcPHgQJ0+ehJ+fHzw9PfHSSy9h//79CAwMtOMR2Ze9ztf58+cBAFu2bMGzzz6LPXv2IDAwEEuWLEFjY6O9Dmdc2OucCYKAn/70p/jZz3424ANlorPX+fquc+fO4ZVXXsHDDz9sw9E7hr3OWU1NDcLCwgZsc3NzQ1BQkM1/94s2sDzzzDOQyWTDPs6ePYvk5GTs3r0b//f//l94e3sjIiICsbGxCA8PH3aZamsYDAZkZmZi+vTp2LJli032aWtiOl8ThaPPmSAI2LBhA8LCwvDll1/i22+/xfe+9z1otVqbhm1bcfT5MplMAIB///d/x5133olZs2bhL3/5C2QyGT744ANbHaZNOfqcvfLKK2htbcWmTZtseFT24+jzdb2qqiqsWrUKP/jBD/Dggw/aZJ/2IKZzZm+indt48sknB70R9HpxcXEAgHvuuQf33HMPamtr4ePjA5lMhpdeesny/bFobW3FqlWr4Ofnh48++gju7u5j3qc9OPp8RUREoKenB83NzQOustTW1iIiImLU+7UnW56ziIgIfPvttwNee7VCaqjj//zzz7Fnzx40NTVZlnN/7bXXkJubi927d1v+9SMWjj5fV1dvnz59umWbXC5HXFwcKioqRnVM9uboc/b5558jLy/vhvVhZs+ejXXr1mH37t2jOSy7cfT5ukqv12Pp0qWYP38+/vSnP43yaMaHo89ZREQE6urqBmzr6+tDY2Oj7X/32/SOGJF44403BG9vb6GpqemG71lz021LS4swd+5cYfHixUJ7e7ttBykitjhfV2+6/fDDDy3bzp49K4mbbgfz3XN29Wa12tpay3N27dolKBQKoaura9B9ZGdnCy4uLkJra+uA7VOnThWef/55u43dEWxxvlpaWgS5XD7gptuenh4hLCxM2LVrl13H7wi2OGeXLl0SioqKLI8DBw4IAIQPP/xQqKysHI/DGDe2OF+CIAiXL18WEhIShB/96EdCX1+fvYftULY4Z1dvuj127Jhl24EDB+xy060kAssrr7wiHD9+XCgpKRFeffVVwcvLS/iv//qvAc8pKysTTp48KTz88MPC1KlThZMnTwonT5603Pl8+fJlITExUTh69KggCOZfjnPmzBFmzJghnDt3TqiurrY8JvoPsT3OlyAIws9+9jMhJiZG+Pzzz4Vjx44J8+bNE+bNmzeux2YvNztnfX19QkpKirBixQqhoKBA2L9/vxAaGips2rTJ8pyjR48KiYmJwuXLlwVBMFcJBQcHC9///veFgoICoaSkRPjlL38puLu7CwUFBeN+jLZkj/MlCILw+OOPC5GRkcKBAweEs2fPCg888IAQFhYmNDY2juvx2YO9ztn1Lly4IIkqIUGwz/m6fPmyMGXKFCE9PV24fPnygN/7UmCvn7FVq1YJM2fOFI4ePSp89dVXQkJCgnD33XfbfPySCCz33nuvEBQUJHh4eAhqtVp46623bnjO4sWLBQA3PC5cuCAIwrW/yIcOHRIEQRAOHTo06POvf81EZY/zJQiC0NnZKTzyyCNCYGCg4O3tLaxdu1Yyf9FHcs4uXrworF69WvDy8hJCQkKEJ598ckAJ/NWfqet/fvLz84UVK1YIQUFBgp+fnzB37lxh796943FIdmWv89XT0yM8+eSTQlhYmODn5ydkZGQIxcXF43FIdmevc3Y9KQUWe5yvv/zlL0P+3pcCe/2MXblyRbj77rsFX19fQaFQCOvXr7/hyrEtyARBEGw7yURERERkWxPj1mAiIiJyagwsREREJHoMLERERCR6DCxEREQkegwsREREJHoMLERERCR6DCxEREQkegwsREREJHoMLERERCR6DCxEREQkegwsREREJHoMLERERCR6/z87JBQRML1iagAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 1 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "performing squish no 2 for state WI\n",
      "clipPoly 1 intersects [14, 30, 37, 42] counties and a total of 76 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 2 out of 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    }
   ],
   "source": [
    "#starting with MN, we moved the \"option2\" block earlier in the notebook, as we run it before running option 1 (as in other states)\n",
    "print(\"for many states we move in outcroppings via clipPoly's before running the wedgePoly solver\")\n",
    "vtdCP = tractCP.copy()\n",
    "#CODE TO SQUISH GEOMETRIES FROM CLIP LINES INTO THE MAP\n",
    "print(\"adding code here to 'push in' state panhandles ...\")\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "#Adding in here trimming ops\n",
    "toSquishUnitsList = list()\n",
    "toSquishGeomsList = list()  #combined list of geoms we will squish (over all squish operations)\n",
    "toSquishCountiesList = list()\n",
    "squishedShapesList = list()   #unit shapes after squishing, list over all squish operations\n",
    "if nClips > 0:\n",
    "    clipPoints = ast.literal_eval(trimDF[\"clipPoints\"][DFrow])   #sets of four points\n",
    "    farPoints  = ast.literal_eval(trimDF[\"farPoints\"][DFrow])    #pairs of points\n",
    "    newFarPoints  = ast.literal_eval(trimDF[\"newFarPoints\"][DFrow])   #pairs\n",
    "    cPts = [Point(clipPoints[i][0],clipPoints[i][1]) for i in range(len(clipPoints)) ]\n",
    "    fPts = [Point(farPoints[i][0],farPoints[i][1]) for i in range(len(farPoints)) ]\n",
    "    nfPts = [Point(newFarPoints[i][0],newFarPoints[i][1]) for i in range(len(newFarPoints)) ]\n",
    "    \n",
    "    for clipNo in range(nClips):\n",
    "        print(\"performing squish no\",clipNo+1,\"for state\",STATE)\n",
    "        n0,n1,n2,n3 = int(4*clipNo), int(4*clipNo+1), int(4*clipNo+2), int(4*clipNo+3)\n",
    "        clipPoly = Polygon([cPts[n0],cPts[n1],cPts[n2],cPts[n3] ] )\n",
    "        cutLine = LineString([cPts[n0],cPts[n1]] )\n",
    "        farLine = LineString([fPts[int(2*clipNo)],fPts[int(2*clipNo+1)] ] )\n",
    "        newFarLine = LineString([nfPts[int(2*clipNo)],nfPts[int(2*clipNo+1)] ])\n",
    "        \n",
    "        toSquishCounties = list()\n",
    "        toSquishUnits = list()\n",
    "        for c in range(nCounties):\n",
    "            if clipPoly.intersects(countyGeom[c]):\n",
    "                toSquishCounties.append(c)\n",
    "                if clipPoly.contains(countyGeom[c]):\n",
    "                    toSquishUnits = toSquishUnits + countyTractList[c]\n",
    "                else:\n",
    "                    for t in countyTractList[c]:\n",
    "                        if clipPoly.contains(vtdCP[t]):\n",
    "                            toSquishUnits.append(t)\n",
    "        print(\"clipPoly\",clipNo,\"intersects\",toSquishCounties,\"counties and a total of\",len(toSquishUnits),\"units\")\n",
    "        toSquishGeomUnion = vtdGeom[toSquishUnits[0]]\n",
    "        toSquishGeoms = list()\n",
    "        for t in toSquishUnits:\n",
    "            toSquishGeomUnion = toSquishGeomUnion.union(vtdGeom[t])\n",
    "            toSquishGeoms.append(vtdGeom[t])\n",
    "        unclippedGeom = MAP.difference(toSquishGeomUnion)\n",
    "        altCutLine = toSquishGeomUnion.buffer(0.001).intersection(unclippedGeom)\n",
    "        print(\"Here is the original cutLine and an alternate based on cut shapes\")\n",
    "        #plotPoly(MAP,0.1)\n",
    "        plotPoly(cutLine.buffer(0.02))\n",
    "        plotPoly(altCutLine,0.1)\n",
    "        plt.show()\n",
    "        # could use altCutLine for a more accurate squish at the squish-no_squish boundary ...\n",
    "        #newShapes = squish(clippedGeomList, altCutLine, farLine, newFarLine)\n",
    "        squishedShapes = squish(toSquishGeoms, cutLine, farLine, newFarLine) #..but may distort results\n",
    "        toSquishUnitsList.append(toSquishUnits)\n",
    "        toSquishGeomsList.append(toSquishGeoms)\n",
    "        toSquishCountiesList.append(toSquishCounties)\n",
    "        squishedShapesList.append(squishedShapes)\n",
    "        for geo in toSquishGeoms:\n",
    "            plotPoly(geo,0.1)\n",
    "            plotPoly(geo.centroid.buffer(0.004),0.1)\n",
    "        for geo in squishedShapes:\n",
    "            plotPoly(geo)\n",
    "            plotPoly(geo.centroid.buffer(0.002),0.4)\n",
    "        print(\"These are your orig (faint) and squished shapes for clip no\",clipNo+1,\"out of\",nClips)\n",
    "        plt.show()\n",
    "        pause = input(\"enter 1 when ready\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "62667c48-6c66-4381-b01d-518af61651bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now apply the squish to all impacted vtds.  \"tractGeom\" will retain original vtd shapes, so we can reset if needed\n",
    "for i, vList in enumerate(toSquishUnitsList):\n",
    "    squishedShapes = squishedShapesList[i]\n",
    "    for j, v in enumerate(vList):\n",
    "        vtdGeom[v] = squishedShapes[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7b967d22-41fb-454f-ae47-d72d712daa4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PoEZHc+KJJ3bo+auvviIYPJzQ3M48ub+Svi4H5ybHH1T7v++vZEeLn9nHDcJuFc2zsLA4RrCMj/9APn7kTxHDA0BqLXz0xW4cjnyWqFtxfXI3u1LGUzTkalwJJ7EoLUTc6F1U1n3Eep/pdr8w7kpuGnYjCTFxbCkvO6xxCCN8oTcOLeLU7zMv7v5Az0bF8hNGUdbYhFNVURTFdLSE7/aNsAfkghUFaK39SoGjC+MjJ9BAma+ZT/LTsSsqdlVFVQQh3SCo6wR0nYZAiK1NXob99kHsQqAoCooQKIrgk3t/iWvep6yY9ykAy045nYvOOZN7L0lHqs1sb9AYHJdC+pBh1K9ZTnMwSLTDEdl+ZmYmCxYswO/3c/LJJ+PsQvG1OwJ79uDo2xehquxu8fN5VT0PD8rCdhCGxFavj8f3V3BzTiojYqIOepsWFhYW3zWW8fEfyDm3380/rrsSgBRXXyr9+1la+AoIgVBUzj73L+GW5kXeFruB1CE1NPvb7vo/bHiDDz98g2/PX4guw8aDODQjQlabxeKU+rpDWq/V+NhfsBXnl7NBtBP3EsLcDykxAjr2+ExwOTEUM2VUEQoowgyaFGbF3Eaps2j7TryaDaHXsapgAQhhtkVQ7a3ALmBgamqP45rUzfLYv/6DkupqdE1nxf13MXHDs8SUPMzmxJFcO8IUN3s2r5Ls1BS8hkFRXQNDUtsySq644gqWL1/ON998Q0FBAWeddRZDhgzp9Th5Fy2i6LrrceXnk/LrX/NUfDopDhuXpiX2uq4uJXdsKyLX7eD2vj3vt4WFhcX3jWV8HMPUvF6A7g2RcuOoDstdtigunXILLYHdOJrSYWIaRkjD5nSxYt0GnOp8DFRCtdOIyn0a1V3E7KaupxxW7VrPmvL9ABRVa53e7xG/33xYMoc1OdI0GMLekCrVieLJxWlzoGAWblMECKESKK8hkJpOcV0ta1csP9TD0gExeiob4/pwSWkz2LJw+bbx41V/6dgoCjJ8Bxec2RU5ycnkJJvGxHolxJaYccwnk5SqSmbufo9vcs9mf4Ofig37cQCrn3qSzXY7IyZMYPDpp6OqKlOmTCE/P58vvviCt99+myFDhnDmmWcSF9d5XKGyMqoef4LmZctwDRuGv6CA1bffwfsPPMXdeZkHJZb2fFEV65ta+GzsQEvN1MLC4phDSHlsFbNobGwkLi6OhoYGYmP/t8WQiu9aBICa4AQJzrx41FgH/vIaNmddGmkXVZNP9ppfR14/Y/8nn+WtPOTtXZf4OLecM+Og2y/fsIq4y67p8r2r7/srxanpPa7/3PpFTJgxDSCSFRIJKhWCwutvwDX2NJJv+ykYZsCpNFoDT0Eaktef/TN6YgaTr7oSr9aMUyvHiYEk3D7s1RmUNYLc9IEHvW8RDAP0IOgB0IJ4HxyKxx7qsulmkcf78hxSfD68QhBSVW6++Wbi0tuOg5SSgoICvvzyS4LBINOnT2f8+PEoYVEyGQyy76qrCZWWEj3+ePrc/AuqHn+cB+PSmHfqTNZOHkZ0L8E5e1sCnLxqG1dnJPGngVk9trWwsLA4WhzK9dvyfBzDOPvHEdjTgAwZqHFOfBuqEA6VRvdqaHdNcdly8FzXn6DfR/D1Mk40ZqDuy8Cn+ojP8FBf4mX4mcPZ1rSdWYWfAzDKP5nbT7oZm2KjpNzLpveKiD3Ow9Y1BWanYZO0NcvECNcNGZjfH3eMqfuxV6nnwTP/wJnDN/OzCWeYGSjhyrFlxX7G6CU8ljMYI1xXxJBmsOn+2gZ+pjmJGj2atJEju93/xhBE211kDunbbZu+hpOEkI+pqR6EEo9Q+iIUYWp9ChCKDaGqCMWGoQXN1wepPlr06m1k732lwzKPHRpD8ZTGjqZ0cAoZTY0M3PUVAonoM4x7f3YvNpuNhsJCnnruOWa99BI/uPfeyPpCCIYNG8aAAQP4+uuvmT17Nhs2bOCcc84hIyODysefwL91K7lvvoF7xAgAWoYP5/O+I7k5Na5Xw8OQkju2F5LisHNX/56NPwsLC4t/F5bxcSwjwD2yD0k/GAqA1CUoENeUQsnqv0WajZz5KKrDDcDm4Tso3V6LKlU8mofsvv3QCvdy1qCzuMZzDacVncrcNYv4nPfZUjaDa066lLjm3ewNNvHPjbXct7W6xyEd9/Yq/nLdNAQCpcpOozOafsNOot/wA2q7lCwkKQbyB3WuIeLavQ8K67G3C8rsEl1D9NJmauJK+rl3wVMv9tzXAZgGkQhn7ooO+ToyHIGSIQwajBiq+18ONgfC5kA4osg45ScMjkkg+9mf4y6dgxZyYpz1d4aecDGNdfXEJyViV1VCdjs7u8lycblczJw5k1GjRvHZZ5/xwgsvMHbAALLffJOsW34RMTwA3pt0MqK4mjMe/wv84+ke9+v10hqW1Tfz/ugBRB9G1WALCwuL7wPL+DiWOUDHQajm6+jY/pw8bQf1+9cRlZgTMTwA+p19Au/vMqdchsb3Y2XVRmKIQSJRFIXpfaczLeskZr/6CdsqdlBRWU2gspSQEuSnmz8jdeYE7BkZKFFRZsl7XUOx2aChgadnbaQgIZsLX1iFHhbtcio2HGWdNSykULpV0gyEs1yc9p4NC2loCEfPWiCpnmh03Unl6F8ipQ6GDkjTqIhog+ggDfPPMB+lNBCy7bn5XqsJ0maKeEadyYBx53YcV0sjvt8dh92+n1rHGJpm3s+bRTW8+uUyGqOi2TJCEqqpASAmGOTbxx8Hw0DTNJo1jRZ/gIQYD+NnziQrP5/rr7/eDEidM4eNZ53JiHXrGHbtj7HbbTS7o3nljEs5b9E8bN/M7/FYFPuD/HF3KVelJzE1IabHthYWFhb/Tizj4z8URVVJ7D+u0/I3n3kt8vySX1xN7ZznqKACeztBL1VViNWS+Mz/Dp99+Q4AYrzgruIMsp75plOfzvx8AgUF/K6bsXiH/rirER7gT2ijpawMlHgoLUGrykIKgcQUDZMIpJlTi6EbaIqdUEvInEpRQAgFFMzXQmAXQbS46aSff2d3h+qoYtSWEHr0RAJqCz894S7mi9PADyS3SdA3eb0kZWTgDIVodLlYUFtrZt8YBq5QCLdhsNvQWfnWWwySkqnnnceUKVPoV1TEkoKtrEtOZruUjG1pYUlWHgGHg9vOPZ3cB+7tdlxSSn61vYhYm8rv8jK+hyNhYWFhcfhYxsexjOCQyqZIKSkJmumvv7nzbhRVwWPzUEEF6gEu+NfP/yfLdq8mqAWpqy/jhdoXiL/yZPpUedBqazB8PqTfT9OXswkVFwMQe/ZM7BmZ5rZ0jabyYkKzvkImdr7Llih0F1nhrayDtHhqn3ySnXcVdb0vwLcnPQ01wB2LumwjgJ+nbYWGrXBfV9ksYc9LxAPT/rWIpPWCwupQXxZqw5krJoUPedgQCj/foZnqoHZCPOAYzVY1n/N5n/mcBsAkbzVRVbvYob/OTzY1oSoKIi1cZVaCU6r85ZTHGTRsKgAtDQ0s+uc/WV9ezrZZsxg7axYz77qLSy6/nJqaGubPn8+3BVt5Y9hYLkpNoN/w/t0cTZP3Kur4praJ10b0I/aQ1eIsLCwsvl8s4+O/Cc28VE7Pn4zDbQpZKc21GBic8NaUsEehe0K2epJv7uhB2PrV3Mjz+EsuIXrChMhrf8EKQrO+QnF0Fs2Sios1/s4GwY6aOqqHjIX6OoIX/BypmlMekct8ODtF6gZsNdfJSRUoqin6JRSBw6kSnxyHFIKmnUk47TqOoSeHp050c5ol8mi0PSLN5YYW/guZj7pGen0Dt/IBDX0mgRDoEip8KoYBO1vaBLpC2GkOno907aZg4Rk8l/MonxUPpDT9G3Y5akCFU0ODcGNHIpmjbKXRLQGNXfvWRoyPqLg4Tr/1Vmb4fHz9/Assr61h3333ceKUKYycOZNLLrmEmDXreKFRMMnWs/5KZSDEnduLuDA1gdMOst6LhYWFxb8Ty/g4lhHikOqmyJCOkGBztsVS9MXFLgx+m3oiQnWGuw1ng4SfaxUlUL6AKaVtVWb9IR2X3byDlpqp/1H4wx91OTalsbnjOMLLBzrNYMvZu/fzbWklQhG8Emz7ymWcMZH8gWnd7s83N3xtptxWSOhQsyVE1JZicpNb8NnjaU4YTdolLx/EEeqe4o+eInPDPfziyst49rNdfLytnAbZdtFPkQr9nJJ3lCv4WWoyS6Lc5ATSmRWSNKdWoDrMGI9ros7hl1ffH0mdbfj7TL5yF3JZaAyTJl3Sabs2t5vTb72FAfPnM+/zWXy8Zg3zly7l/NNPJ6F/HjRW4+4lcHRRXRM+Q3JpWkKH5bv2/B2H3UNmxhWoqlVQzsLC4tjBMj6OdQ5h2sUI6Ug61kxREDjQueSkB8Cd0OV6vuXLcO/8gqrgUApvn0UIyQynaZwknfIb4gJeztuziHqnB0MoIAUCA0VK4m1NzNzyN4oevB8BuAN2CsmCaf9gcUsiQ+Yso97hBuwohg4KePwtDCvdQ3xKz3fpwgiSH1/GyMvGowdC6EENLaDhrQ+wazVsr0/j5IzdULObkj/PQkI4fsR8NMIGVuuyTv236aoywdcEwEkPz6EFN8d7ojjvuCyio+0kRDuYMiYNw9/M+icdLIkyA3wLm/sT7bbTzw2eUAa3TrqGycMO0EkRgqE1Lu694zV6Im/6dAacfDKrX3mFWYWFvD5/PgMTMzh/mZeFWhObHeXmvkhwZ0Rxxw/bhOdO7xPHwCgnNxcU8t7oAezxBVhSvpUZVY8DsHPn/Qwe/CeyMn/Q4xgsLCwsvi8s4+MYxhfYh7Ijjn1//IRIvEI4NdR8LmGoj9zLLgNg18btIMDRzvNRWbmFZhHFeW9Mxq7YUKXABlw84FwuOOl+AGzppvy2sPlwpPiwSUhrclEuBfWuWM6N9dGQdTpmdER4CFKiA4OD/2KAWs2a1HEYNjtj96wgiQKWLLmKl/v+lMr045FGCzcO6UdabAwby6tIKlf5omgXtskdC7AdiABcqUkkjutcin7I5RBsCbL47y5SNJ2GnHHh7BVTaRXCj1IiMCJjjhzCCKZ+SUFVM9u9QxifmMBdlxzHoP7xnbb55rZPeSR8rK5Ku4o7f9h7kKuURqespW73VwjGXHEF2+9/gF12G8tnfcuIwjy80QqBZPOnmrTfR6jYBz9sW89jU/lgdB4jl27h5FXbw0vdTCQKJzo2Amzf/lsyMy7D691BdHR/FOXg68tYWFhYHG0s4+MYpmHINxjCTmzsyHD9k3YBkwL0nQai2PRy7N+1l7e//giAz5bMZsDQPOKz+rBU6CiKZJAni3jVjY5kadNe5pYu5oLwdhSX+TWIOTEP5ykXA7AcuPiPX5MgBL//7U+6HeOqp7+BKkiu8iHdblTMqYoBWhFXG/sZcsptHdpnxniYu2EFAIGW7uXcI8K7PQiCOaIc3JiWwjB/H96+ala37Q6Gf337Af/cfx/zzh1FakJ8l21OzJzGXzY/xBmec7nz9IPLrpGGYWboHCQ2t5urHrif4uXL+eK9uYTI47wzYhhy6nEAPPbqBrSNnWvppDjtfDomj1lVDVyUlsDQaDdvLB4EtkT6aavQtCbmfzMIgKioPCZNnIOu+xBCsQwRCwuL7x3L+DiG0eKrsU2Npd/wrt3le55/E9u+ZPY+8DEhOl7IH3/xKRITW4jyemjBYNLwc7hw+C0A3PvqZD4J1fDDl0cDYfXR9FTO3L+EK2mLSxicEMUbJbWc+ruvIrVZFAQKoIafr/VfxKVqIr9yzEFtrGZX9CSCtZKAo4nle518+ed/tBuVaTx5g2ZsibfO38POa+RFuYjdXUfRHW/T3fxTvwFJlLkCXPnqJZjmmUAxc0xQwq+rNZ1d/hDJMS5zWTjbRRFtLSu1DSDg5bt+TR9H14XYmhU/jIXZ3k+R/1rcFjsjBEKEtyYEMhBEa9AwiGFefAkj6g9dcyNr4kROaklg7rsl+Iq9keVG0MAWlPzl+XU4PTZ+fmk+9nB2y/h4D+PjPZG2Oip2NPrmXI+3eQc+XyGNjRtoadnF/G+GIKUpEz940B/JyrrykMdoYWFhcbhYxscxjMQIX+q7Ju7EPOqjChCGgs0QXKUPYHFlJfsCTWRlhVBVO44ondktO3CXF0aMjwtHX4+x7Z22LBPD4FO1gmhZSftL0J1XjSb6jQ00+EPoEgzMaqkGpoy3LiHV8xHfuouoTDyOFy99ke3zC1j7QTXNSTuwRXWdcBulJBBsloS83QuIGYEg/ZwKLncy6CV0nHYi8vrCuilsTKkA1RE+YjI8kdIqCS9Z09KMxI6uq2iy9X0DiWbKxyNRtVwCfg9VAQfx4WrAB2JHMq4pRMguqHe2QGv9mNZ/YQl6GfJhqJJgKMSQOjfTkyZ2u589EhZhE0ZbLZmcAfHs2t1E/FrT+7HzRC/5WV3HzkhUFKmTm/vzyLKq6q/ZvfsR4uMn4GvZR3PzTrbv+B3RnkEkxB9/eOO0sLCwOEQs4+MYRkodenDZJw0ZT9KQ8R2WdRYzh3feHAUMjbweO+pHjB31ow5ttr16Llv1/fzsn9e2q28PxAKxIhy20FF4RAAhbR0hRWNNcC9/vf9N3JUpKDi47Efn0Xdg17VFqoqaePeBVdh6yOJQPdEIodDUN5ahN57QbbsfcVm377Xy95fW8OzOCpY8dFa3bdYX7Ob817Zx8g9TOOfk7i/CVb/tTyg+j4wbvuq2TfOfZmD3FuB4eEevY+uJhGRzOsQT3XbML5veD6b349NVxRS9tAN7DwHJAh0pOk6pJPeZQXKftqDYkL+KDV8ex5bV1zJq4vvEeIYc0ZgtLCwsDgbL+DimkT16Pg6F3mIea2wN1NGIgdGhqFz4STuTQ9LeOjlODCdD5POhfJNAo0Ksx8DmDJCamdjttrSwjPk/Sqp46JMm7BJsCOyAnfBzIUjOtXOy7SgUXTZkN5M2bUTiMnpJbRbSQIqeU1+90sluMYTAU08hpSQ7P5/tYiclVXswQkGEbnDhqbeQktGVqdh+TK3POn8HWpcs3VjJwOyuPR9moG3P3x/jn2cyrryBrxnGY4vf5vrrrycjw1JItbCw+G6xjI9jmMbGjRiewBH301o8rSdUh414NZ7nL3/1kPv/YPZXfFjxJqdfO4Lxw0f12r5MNTU79ngEUpFoQqIJOv15BzuhxUb3fo+DRPZsfOiaztdrd4Wb9mx8KKJ342OjI5clRgpqRQW6qhL91Rxm566hyl2FK2jgcwqUuYLrf/hEj/20JgjLLj677ORo9gM1XxbDzIFdry8NJOZYWypLqN+yMVzrxiCow1rFwbcuyYacTKYXmuJxzz//PHff+1uclkqqhYXFd4hlfBzDGIafxsYNbJtzEnZbAv1Peg+hHvxHFmzaR+XGhzGkhjC6zywBUIWKLvUe23RHbIobKsDmPLgLllTC8RqpCdx2atcXToBhs9ciQj2rex4MitFduKrJ+bc8yqZYM53XW9NzVd9opYWg0UOgLEBiEgnlzdx63yPMfuwxlgMnVJxA7tAYfvjDO5j4wkhCtlDPfWAG+EK7enftGJWbwMITU9BXVnW/PjqEDaWKTxZi350Vec8OTADe65uNR23m474fM6xuGPHFVfxl9nZ+e3Z+r+OzsLCwOFws4+MYJqs5mSp7JbXaPnz2Ivxzp6FG5vDDCqUH1C8RpqAFSChX9hKygcTF6tISbn/jnkiGhkCwQVtJg6hlcNJgavw12JWeK8gWemv47Zp/EjrAkKmu2gzAh/N2880SHbtT5bqLhuB2dP31SrSby/u5eq5qC6BV+yj68mPa7VybE6dDqRYzb0WY1efM98JZKMF6hSCS+95ZikMV2G0KDlXBrgocNoUaV5/I9jYX7mXrig/Cnbfm9ijh54J0PYFAtc7+L2aZxe2AGq0SR2JrBk8TS0pVIJp3v30XMS6HIbrOtoXb0OLiEEKgSNjVuJdZr71CP5FjjpO2fRJCYAQCULIHGELxHrDN3d/6sYIMC8yWtSCB2ZtKI7NFTf5mWuwhDAWkESLFv5otW97G7vWjp++n30/Oouz+LZH9fXT/Lyl2VHDdgD+wMWkj8XY7sxbv5fZTB+FxWqcHCwuL7wbr7HIMM7g2hcFRQ/CfdCtbVl1NMzUd3m+bTelKPEtgN2zEh5JILx1Gecxe1tlWmlkZwszOqLdXgYT1VesBCOpB7vrkrnY9tLn7myRsMKqpb1oOto7xHMLQiA2kYd+rYITqUH0G68emMmlwcpf7JcK39L1GcwgdiQEL48M73GpwdR/HcGCfEhiARoLi4611VegIdETHWAhHm8S7vmE1X6zq3vuRnfx/VGkD4dP2S3OIVxWuTP4FaxkG4WJzBd8WdFg3ymXWiEkI2JmXUMw8+VduWPq3Dse5bdQOEuoURAJsK4JtRbs7jUUFWmIVflRd2eVYb5Nx5LKd8op7yNRvJ6TForqiiVHfJmCMRolXqWvKRdoUVl25inPevoESRxkAS3ZVc/qw7qXvLSwsLI4Ey/g4ltGDoDpxJY/huLM2H3Y30z6aT0JsCz/4y9kdll/72K0UxK6CcAyGRDK/Zn6n9SUSv82OIRTcUcNYdfFbYa2MzizYWMHmZ7ag2g4iULYX68NweNGPayT7uvM6rypl2/rtvD3SMOvAGIYBGEhD4v72Tzxk/5CpUzeY6bBSohsGgZBOUDMIaDrllTsp3HMLmTGnMCDvBlOZFB0pzMJ0plKpwZx/1JOSXM4ZV04HKVm1fx1bX3dRr2dRccNCshXBonk3UxWqZ86Fc5CGxDAMhBBkJpgVgT+4bgG/ef6vzIt/nx/cORSbUM39MSSzn1hBddAMIM3MtDPRZsM2RBBz8ghMzw4ghOnp0A3qHfBjhzm1IoCXX3mF7LhUpl9+OsgnidYb0HWN0iU7EMIBNidxDzwdOY5b/vE+okbHZXPhVpNw2irQbQo3vL6GNfeeQpLHEiCzsLA4+ljGx7FM4TLz78LnjqibaLWegTneTsuHF01mlJzGbU9c2OP6O+oaOHHdHn7h0Lhnas9aEIZuxmgoPaTXtBouvXo+pIG3eWf3fXTYhGj3v9rBN+KOi8HnM3C73d1uKsHtw1dbhydhMBn9JnU/dvVdnHEaMZmmV2DxY1+TRAZeRz19UqehKirZSf2prlxHemzXqcZudww5aVlIv0Kt28XOiiCVlTXw0S68RhyK1Ljs1yNxB3OpebUET6KN+H7xXY/7gNexwQB9DMiNqLSa3qdKexF6qIuYHh0MxfzMWj0ws26Zyil/Xcgpf13Aut+d1u2xsLCwsDhcjk4ep8V3h637C+aREu2pwuloxu9v6rZNVXMLZ67dCUJQEpvIO2U13bYFkOFvlNKj/kRr497HqNo8vTc6CHpLNbbZzDt8wwj21lOHvlSp4o2t5pJfH4+qHHyGyJw+eVTnvMrUrUVcW1vBnTaNT4elohghrn/iJBIHpCEDprEg7Af/MzUVVzsvl5JO3qpgKACGRJVhz4kwK/fkpcQwc2Q6dS0hzv77ooPetoWFhcXBYhkfxzIZY2DU5Uelq66u8zFxFdhVjSVLRzPrizO6XG/6ym00K6aD7MOaJn61vbjnDbXGc+jdWxYRz0evaa0Cpyuz5+0dBKKtHF63qKoZ/GoYvWShyMh/AOjuIJ7GPjQ3tWXACESvhlVOvPnTOz/U9hMcZt/Ljc+fjhoOxJUhM7BX2A/eqOkoA9dx4O1tj7raavb/fhEDStMiZ4H2/qi/XmqmTG8uaaTR33tmjoWFhcWhYE27HMPsCSawdZ8kavaH5gIhIlkdkeyW1teIcCBnWypI63u7VcGALjJWo6JT8ZZ58JYNByGZ/flxSNso0lJPCm9KMEpvYZ46IbJOiiF4a00xHWc9BEr49Y7yJuKAPavKYU9TxJXf/oLYEL6Y9WSgtNKbgXJwKGZ2iJTdxqq0Gh+hUDPBYAtCUVGEiqKoB6zT0bNwxg/GsOrpagr27mTEUDNt2GwvCfqaux1RstIExLBd2Qv05Uf7d/DH6zvW8JHBcFaR/VB+pqLLY5bU0NGD1tTQgNtwsmNYJQOnHhdeU9CqiOK0qQxK9bCjwstLi/ZyXN8E8jNi6WPFgFhYWBwFLOPjGGZ68U/NJyUHu4aky/veKAeGL6aTWJc7VqC1JFG86FYAotM2kX3ik9TWLYi0uVaBi7RY/mz7I0VkUywMbm/sPhsk1tC5BahcVEHXORhtBGt60cs4SrQZDx3VWdtjt7sxDAWf/3kWLX6+w3tSiohQm67/kZaWlsh7ef2zWUU1it72U4rdW4Xhlhz3bvc1XXRbCrakn1HqdzG4bjdXjO+sqyHDMRqKo2fPxzP3P0FVyKz1IgX066YSsN5+Liz8NDE/i+x+A8KLOk4p/e7sYfzmo028uGgPT3xtjiU11smwjDiGZcSG/+LISnB3a9RZWFhYdIVlfBzDDE71kJ3g5IGZA2ktYmamdJgqleYMgLnMzPJoe9/MBjFfT316KwFPZ8nsU6+4juOmlyKE4MvnlqNpyaTFPW1mhLRKkkvIdMTwsrDxh4I9NPvTeXLmCMy32i5mhmx7LYbqxMm2i1Hbnbg5HVHjC7DwmS04kl097r+gd1n0g6O98dE1iqLQN+dx6up3m8e29Q8DaZgpv1IahEIudL1NrEtRBQYGu9dW8nrLLM456wSmb7UztEQn7tJLut3e9s0LGbT694zeY44pe8XiTm2MiOejZ+OjNtTIgJhs+vXNBWDIxJGd2tQ5WzDibfRtXeAwj4kSbF+rp+OkzdSBfVj465MxDElhbQtbShvZUtrAltJG3lpZRLXXVN+Nj7IzPCOOYZmxjMiMY3hGHH2ToiyDxMLColss4+MYxqYqpMd7SE1OOqJ+YsS2LperqoPkjFwAohIXUF6QxbcvdNUyBIQ4mXjcCYUMTO0+G+SgaI2P6MWy6D5+4dBordsipYHoQRp90KCZPfYjpWT9G3OJimmbwoh1xhLsW03M/gway+D5glmcM2crA4Gh7/+h276qZlby5XN3s196cGTnMDSui884HPOhOHoWfzMw6JuVzZRLZvTQRqK0MwgJT3nJTmeAzkdcUQS5faLJ7RPNzJFtGTyVjX42lzawuaSRTSUNfLa+lOcW7AEgRvj5eU4VGRnppKWlkZaWRmpqKi5XzwanhYXF/waW8XEMY8g2ie0jpbfQiZk/vYCyfTs7pIW0v3Ntjd1ISBl+xGOJ+CF6NT6Ojt+jbYtHJtVeUViPIm0Y/jYDRhEKv7z7cu658zkyGgYy7tQBlFUOI/2bLT30BMnRKVxzx0s9tjECYePD3bMSrIFE6aFCMECD0khadQIr//ARAoHNUEgmoePnjXJIRzwl1sX0WBfTh6RGllV7Azz4wXI+2Ap9klMoKytjw4YNYd0VSEhIiBgiaY4kBgwdiC3eaXlJLCz+x7CMj2OYngIkDwXTg9DzZcUVFUO//LFHvK2jzlFxfYS7OsK+XFGmB0Lt4uY9vsXU/Zg+dTyzv4qlPubIE8nMgFMV4eo+yFPXdRDmtFFPfJLwDcP8/clOyDHtDUVQ66hgUn5bllNXOrmHSh+Pk6w48zjNPPtsolwONE2jurqa8vJyKioqKC8vZ/my5fgDfi79bBLx7ljsGR7s6dE4MjzYM6Kx9YlCqJZBYmHx34plfBzDGFL2qk9xsPQu6CU7PJoKn0BrrRTapcgaRrsew1k1hzLQQzAGjorvI7JPR9ZNfLIHqYbwt4uTXbe1gKVPlBNFDM19TWlyhIiUoTkS9AYDUFGc3U+7tIq6qb14PjZE76Q2zc8rl/6q2zYHxnwcLhE/U9jbYbPZIlMvrexZvZ3XPn8L17QMPPY4gqVefFtq8C4KR1fbFOxpURFjxJ5uGie9Bd9aWFj8Z2AZH8cwihAYXZU0PUQ2uK6AapC/F4iDvCq2NyV0aUOTDmon/o30sy6n6oFTSNHXdLuulK3pte2CTmlLA04Brkuxs6TpH0C/7gchNeobVvP1/Dt6GWH3eyAEBDSFnfWDueP3s0zNj3bZsh2TaGWX77Uv+naB9CC2wBu3mhlB9WEhsJqoUr5JeoXFL/2LSWUVnNNssGNyWB1UCBSjCkXxgdIq6BXusMMA2l4LQOT9DDVpBHv/XoB2oHERbhdCAwF6sOfPtcJWQYWvgis/nBKukivDk1ASmzeKgTvPY2iwP0OMATzwy286SNcLwiJl7fxnsos/AzPbJqQbnIa9xzTp1q+hPSua2OE5keWGTyNU5iVY2kyo1EuwqInm1RXmHKQAWx839vRo7Bke0zBJj0aN6b1AoYWFxbGFZXwcw9hUgX5UdC7Aq8TTOOi28CvR8YoaedrxcisRCKkhZIikrX8lZcVNhFbcSorw06KkUT/kJrO5bHdJai/C1ZqJQ+vFxkBKSUgLkLv3UeIT6nocswinxiYkTCaS5RNBHjCV1LZt2S7rBySF1XsYlrSdyVkODGnWUTFavSEHrC7b7U77562vF3h1TgAG9jGVV+PR2GwU4M/dxonqOAQC+ygv1aEa+gkzK0b4KnF4t5rbSBnaoRYNkQym8NjbbdSo+ieK/TyCqdMQqsKBuwughY3TFtHztItDQFCCU7VHqhqbto4gb/PVRDflUJ9VTCAYhao4Il8RobSl4LZ6vjqoych23xZpKoUEa1vI9tlwqN2fXvQKnzn+uo7p1orbhrN/PM7+8W27qhmEKloIlXoJlTUTLPXi314UUYCtG/QVgQF7SMgagydmGDGefNzuHCuOxMLiGMYyPo5hDKPnGikHS7FIoyj1NCZdfvth91HxdR5aydbI6/iTLicjp/9h9VXjrYdHH+1VuVMIGzExYxg7pvuskYNh3+LnIPgXnrr+dFS158yR3ph6z2xCKR5Ou3V8ZNlMJve80n1xAASO/xvOmT8+6G2Vffoq6Wtvoc+tN+KIT+yyTWlxObz4DY1a9xL5APenKDgdJzF9+hOd3nv6C7OY4G9+c3Wk4vCR8PzDbxPam4LSQ1/2xHDgjLv3U5CwKTgyPTgy26T2pSHR6/wES70U7nkQn74dX9kegvv/AYDNFoPHk09MTD4xnmHExOQTFTUARbFOeRYWxwLWL/EYxpDyqBgfOjYUeWQS2akzLgAuOOKxAG0xGL3crZu7fuSeH3s4GNOQkiONGNB1A9FVgbYe0C6Zje29M1BXP0xw20dw/A04Tjy79xXDngND6/6z08LpuIbseUyKEsRm71wnJ+jTIs8PxvDwVdRSOmcZA67pnJYspcTw+8lJSmX3XhmJ+egKNTo8VWI7vO+3UAS2JDe2JDeiUCXBfzJjp79IIFiNt2kLTU0FNHkLqK7+mqKiVwBQFCcez1Biwt6RmJhheDyDUBRLtdXC4vvGMj6OYcxiYEehnyPv4qjSmtAp6W3njpLEWPgg6obBkfk9QAeMat8hrWMbNomQnIvy3qU4mhbiX5cMB2F8iFbjI9R9sbuoqGgA+iSkdtsGQAgd0cXet88oWfLZh0w5p/sKx1JK9k2bAsCa994jGJdOY/pINM0gEICqYBya6gKhoOhB0DWg63gMIxzQ7PMf2rHsZmS0Tv44HX1wJk0jKWla5F1Na4oYI01Nm6mvX0lJyVuAgRA2oqMHmgZJ659nKKoadRTGZWFh0R2W8XEMY0gZ0df476LV89HzvgmOVJnDRAkLi+nGoXksusIAXKnRh7yemjsERICgfRSOH//1oNYRNtNYkFr34277fnRvqLV6ILrKiLE7VH729Im8/cjTrJ81gvWz5hOVugV3tIvG8kRsziDJ/X00VmvYVjfTqp0atXMFUcCesf2Rbg+qIslLbiIuU6Fh3Wri1s1HdBL0bz9wc9xuR9eiYzuL63lsUxGtfhkpJTYh+NXIHPIy4zq0bXFvRe9h2slmiyEhYQIJCW01inTdh9e7naamLTQ1babJW0B5+adIGQQEUVH9w8ZI67TNMOz2uG63YWFhcWgIeXQqdx01GhsbiYuLo6GhgdjY2H/3cP6t5N41C4AR7s4n6AM/tZ4+xKdCn+JkMA53TK9tOwSgtmvoRefJpM+pCpZwzq5E1APMoq6SN6DNc9Mxe0bH6a9m/nCNlbnjTc9E+E5YCIFAQQiVskCQLKWGkS4vqlCwCYEqzDDUhkI/IypiGeE/kUxjBHpmJRgCYYT9KiIcyCkk/lALgkaK/ONAqKAIZGsApWIaQUIIpBJeJsJTEIqZQtwqDCoFfLynmjoMxvRrVSQ9ICKVtjhSIxxIKgGjogCntgwjvj9EJ0XatH8MtGicpuylv73JlLevK6SvsoQ9wz7HVxxljkcJpzYrAqFASzDAZ7VfEGNzktYnzpTGl21S/KbKvkFW/lO4Hdcw5YTfdfmpBwM+Xrh1GQDO+CIUxU6wxYXuj0c1WsgsXkLeno87rTdo9SpUT8fpnJV/fYKY55/l7et+iWG3d/oCCEBpaWB5WhpZ9iyiPB5aayXK8PHfYWhscsMYf1uQ61qXZLRPMESxmYcC86/S+T4TWMb10+d0uW8Hi2EEaW7eZRok3i1hw2QrhmF6Z1yuLGJihmHbpZFqnEzU4JE4B+ahOK1pGwsLOLTrt+X5OIZxI/B1Yyq0XdTbK1S2b9D2OqCfjk0JIdT6tnadnA6y3cLO25xDCfOit0E0TLcnkixsHZI2Ir20uwC3f89o91ozBHsbU6j0lqPrXvNC2SqBjsSsraLj0X1IvY7tIT+alJQGAm0bckCgIcRM1azIqockUtGRaquvRJjWAgK74qbJH409JBAYCCkjtokSztYQMpwMHH6tHPgY/ivGYBM6u/Z1X1wPiFT5bT2iikxEZSqiHpR6M5OnNabFbCfZr6WA2MedzsVm+qwq2ZCZTVPDayQFjketHxrpMzJOw48ivDQ5Nbwlzeb2wh9C6+dsswfJFpKQt6zb8Tqcbm56djqGEURRzKmSutVfUXLvL1H2BWj/KXtmzCD+ootwjzuuk+EBsKEyxFTA31iLYbPR1fepMDGJ9TmDWA8MDRqI8HejNQVXKIJLNTt/mzksss7NczazSdVYiWam9SKRAkqYiV8ZyvU9fSAHgaI4TE9HTD5g1uWRUqelZV/EQ9JQu4aquPUEnlqAq0ABVcXZvz/OoUNwDRlK1HFjcY0caWXaWFj0gmV8HMPcY0+g/5hkJl+Yd0T97LxrEY2p0WTfet5h9zH/5bZg02k3/ZkBeZ2Llx0stQ2VvHL9jzl7xI+47NybD3q9//vXdczRlzNEz8an+bjv1/+k5qnV2DQ7+bf9oPcOjgLavXO4KCmex26fctT7Hv9/X7A35gxif/8wALs3LaO66ipgPrVJ5Uy5oPPl1VfTQPTPn+C0i37OiEvP6rLfxsbtrFr9IQ6Xt9cxtBoeAOVX3YoKqD88Hv3VVeh9FIbMW4nN1fO0U2mLeeF98O5bULqp5fLM9lIWlFZyd2oyt+Zn9jougKdO71ra/9SFnyLsRxrN0zVCqERHDyA6egBpaefiLS5gxY5zSLrhOpLTTsW/dRv+bVsJbNtO09x5SJ8P58CBxF96KXHnnYv6P+69tbDoDsv4OIaRHJ2AUzj8jnxBH/t3b2Wruoshal+26ftxuzrf7R4KajjdUfaQDXEgdfVVLPeuBTc8e97LJCWZapnVclXvemNHkZAE+9EquHMAAmiuN707WzY9TEXZQrCBXUvB1k2KcNsx7H5MDlsKAE5x6HV5ymOjifKMwbhhGNKAlU/93azyqxsgJdIwwlWQdTAMpGEwtLaYkngPg3voNztcLC/VduSKpb6QTn2wjg8WPhqeKWtVHpFtU1vhKs3ma3O50RRiqNuBx6Z2Fntrh5QSozGIGuMg5K8GJwi7A/eoUbhHjWprp+s0L1tO/bvvUvHww1Q+9hixZ5xB/GWX4h492vKGWFi0wzI+jmVk+6mQw0dweLZHeVUJp37RVvtjm74fALs4sq9NR5n23nll3pM8s/dl/G6doTKHxMS2zA6zUu33d1LfpWvsKqvjoe+gb6eq4EowPQXlVc+DDULeLFx2Oy3OnV2uI8MiYz3VdrE7zSq8uh7otk2X6/3mctbOWgWLv0YYrblJ4Smd1umRyLK2CcCQqlDUN5Wpuk53NWxbTY7KhgYgrZtWB4c3aKePw4fL//KhreiCKgn1oZ6/PzLclhCgSpQmUAKdDXChqnimTsEzdQqhykoaPvyI+vfeo+Hjj3EOGmR6Q849x/KGWFhgGR/HPkfhuurAvGM/VArKO1dmFQbYelCuPBiUiO5G78bHqq0LebzoBYbKbP5wyl8YnNnx7l0erXzkQ2Co57spC2+zKZHUV8N7IlIp4ZTpn7Ng5VBzma6hHHDsIwZcD4dAUZwYukCXbdMuhmGwe+MX+L116JqOoWsYuo40dAzDwNA0fOFNTfvBDEaf+COEzYaw2UBVEaoKitKl4ffavz6k6rOX0XoYVFRDLaJF4yG9ib2z5/Onk6ficR6eTLrPSKcskMnMsw5+Cg9gxF1fcN2QNG75UfcFFWve2oZvQxX2TA+pvxiDf8c+9p57Ju7fp/fYtz0lhT4/u4Gk669j18uv0/L8swTuv5+K++8navp0POddQMKp03stCGhh8d+KZXwcg+xaVcDi95bTWNXMhlqVpqpkjGCQGOJITswLZ2uYWR+rWE2lq55WIfO2TAcwwnLm13AcMaVeql9rZ0yE3dHN5dX44nxmNOUBFMgdHHjrqkqFOR9/jM1u6yDH3lqrRCKp9JXjiNIQillHRYkEk5peDy1kimZpeg/iWVqI5778C6+Wv0+c4eKmkx5j1o5qZu1YGBm/QBJKcuOxxbJu8R6zBl74ZK4Ic0yBxkZGNjYQq9oQqooQChFts7BLyBx6uwjR1mmVyDIRycbIQBAyDN5aUYhEYoRV3E3J9rYMF6M164TW50SWG63taVtXAtWGDjU+3vxsO2VVaagxVdR++yblzUNR/Yn4P9pByAgQH6wmI8aBzWXH39xsDrWHi5gQAt1nR3PURZYV71jEpw8+2+06rSh2nYT+g7AlJPTaNrK98ONrs3bgdrnC+0jkeymBLYWFOCp1hufW806/QXzx5WJeGJTJifk9TdZA3dp1zF+wBNvo0eGPShAy7NR4/bz1+hzOPm8qMbGHngrdFb5ttfg2VGFLdpN8U3h6JbwPzUtWIwNB83cjFKJGD8U9Ig9/o5fKkgr2bdxBqMlLcM6X5G5a1kHcrmX+fFrmz+fhaT/m3HPPZ/KMfigu61Rs8b+F9Y0/xvj65X+wfs6syOtQC2yaZz4XCC7J/VXkbrPaVs9fBj4IPlANm9lCtrZsfRT8gNHYUPEX1Hbang2FqFpnWxXbdkxyDOSdfnHU2xqQwoEwDOJCcWwrq6D7hF3zKu0s3Ira4u1479uaWRJeWiK6zxi58fUrWa5spa9M4qHTHmXmbi8BNabDZgAYHdZeCDV23ZEKt1TauGZfCNNvfvhIoA5JaUuQuz/adER9dUejCr9ZsguYGv4DuDH8uBeALF8JF5R/2mE9p6fnC26oxY63pYqiHQsAhcoi0xCdfsO55ORPRVFsqDY7QrVhs9kQqh1FUVAUBzbbocX41O1oAOCvq/ehKd0HggpgxMKvGL3qKz499TKuKqxj3JZ3mBovGJ8/gKDUCBqSE9JHEW03p44+eOdD7j3jorZOJOABtSbI3ds0Xl77AXP/ds1Bj7Unh2DDrD0gIPnGUREPhZoQC4oN77w38c57M9JWScpm29gJDJr7PgDJrcfCFcvOa27h+LNPAo+Hqi07KN9XgtLSzLdVKdgX7aPfiiqixqbgmZSO/TA0ZCws/hM5IuPjoYce4u677+bWW2/l8ccfjyxftmwZ99xzDytWrEBVVUaPHs2cOXNwu91HOt7/aurKSlg/ZxYTL7qC8lXb2Fe4DoC0xP70G34c+WeeQlxOuhnsp0t2b1sAm+CGvj/h5pNu67bfE1+awsy6EznTOQmncKG4bSgeO851UBcoZ8TfLulyvRO+Wsm18o/88fTpALy+fDW7Z3/OdXfcQWZc1/PWn236jDUfrCH2qhO5afpNXbZpDDQy5e0pjFJjWbBiDiBobPayr6aIrH45KIpCkbqVmd4+/GTyzYjGIgJqPwBeGuhEomIgiLZHMblPelulVWkgdYk02oIK85dupDGpkrjzJ2FoGroWlq0Kx0rIdjnAUrZ/bBXooF3esCT61WIGxju46cIp4XRaU29DAKpoK9amiPByIVBb2wkwnUHh5+3aKQhA4lIEqqIgkag2HVVxmN6asBPmwt++ht0I8eNHnkP3B9H8QYRQSB42oNvPH6B4cSotVRoFHz3SYXlC2gCS0vJ7XPdQGZgWQ8F2mHPdZDwJpuGihI9Fa7mANQVVbFu7DlEdTailgZ9s+DtrpkxhS9JIlops2AGtkSH3eBfwi3wz9ij31BkAvBkrGJiaEk7NltgGpDF52xp2OpNYt2gdY04Y0+s4JRLZonX7vlblQ41zoEa1GVD2lCQGLl1KYF8pda++T/PSeRgN5Rg1RfSbV0rZoNEEppzEsDNPIrZPHIP7JKI42qaT0vtnR4Tafv+bL3GkROPJz6B5ZTnNy8tw9o8jelI67vwks5ighcV/KYdtfKxatYrnnnuOkSM7plwuW7aMM844g7vvvpu///3v2Gw2NmzYYM1ttsPQdaqL9qOoKklZbdU3ty1dCEIwaMwkln/wFm7VQ0gGaWquZee65ezduAbV7sDticEdHYfP8DOEGIYPG9rj9mRYSyK2OJqA7sOmqNhbP4548wRf1+Jj8b796LqBpmvohoGuqtiMNt9Fq1KmrYfPMic2hzWsoW9s3x723+xnQ9Mmbt72fx3ecxVIzogL8assDSiksPbXAAzkAXaKIfxkZ/ugyWZ+l7Ka07PGMiAuG1A6fKNbNB1dtRHvthOTlszRQKgrSXUanD7syIIkD4fGlkYS3XZqNCcJOQeXntpKoCEaV6ydU2+8GhmuA+NwRZMz5OSjPk53uMR9anI0nviuZcpPnZzNqZOzqSoZzbo1t6N6tjOC7YRaHMSlPYjMHEiU3ckZm7z49Tb/hMvtgiD0iY8jO6tj3MW4lhJWR2WyZUfxQRkfAFplS5fLW6eI9IYggcJGnDmmsW0EQlQ8/ByNH73UoX15YgZ9n3+ekcN7NgLbYwCKQyXutFxip+fg21KNd1kZtW9sw5biJmZqFq78RLzLygjub8Q1MIHoSekgQa/zY+vjRtis86rFfyaHZXx4vV6uvPJKXnjhBe6///4O791+++3ccsst3HXXXZFlgwf3PI/7v8TOlUuZ9+IztDTUA5CYmc2giVNIysxm1acfkjFwCKLKQCDw6V76Z4/FE5uIr6URTQuiBQLUV5VTXrqLgO5nopZI8/iKHrcZlH5qE6rJ/T/zrlHXQgRb/AhDkhF2198+byGzYw6oD6KopDjbgj5ajQ97D8aHLZwJo4ruUyhlo1mr5LLA1Rw/9jQa6hbR0Pg6ij+O3PQ9AHibB9PfnQW2Fuz2FJ5W91Cv1EMoQGPVEmpdPu5y3McfK/vyWe1avjwhm6amJkqqqmhGYAhBZZMpuR10Hr0A0a4F2r57yuvKmfLwSnRSmGzr/m69OwQqUTFJDBp77ncwuo60Xrg/f3ce9d56DEMSH5fAZdeejdoutXbjijcpr30Y1eMlc+3tOJtyECg4ThNkpA8j0FRHaqDSVKUNo4Wf2/SOkvOb12xldVQmZxtlXHHV1WjBEDZH79ofjpyYXttUPbMBgLTfTKDx8/kdDI+deWNwTzuJk275EfZDDJiVsl14kU0halQKUaNSCBY1UffJLuo+3gkftrUP7Kqn4cu9HfpwDUlEzXbT6KojZ9KYDrE/dWUlbF28gFGnnkldeSnrS9eyPmo/H+z8gKkZU5mQPoGr8q86pDFbWBwtDsv4uOmmm5g5cyannHJKB+OjsrKSFStWcOWVVzJ58mR2797NkCFDeOCBB5g6dWqXfQUCAQLtlCsbG7uZu/8voKWxgdnP/I2MwflMOP8SQoEABQvns/6rL/A3NWJ3ujj5R9eT1G8AP0l4FiXKRkzf7guG7di3kc/u/A2Ku2etBIlEdbWdiFWbHXdsxxOzV9NJq6vglVF52Gw2VNWGy26nf2pKpI3eQ42QVlq9OEYPVVm8dvPi9HxmIk81AbYTIPEErjOeJhfT+PBEb6eS7ebt4QEZou5YyASe4qc8zV2UaikM/WgudfFdezeyY45Ml6Q9IdTvTOejJ/aWbUBHJRnB9ICPF2/5KT998sVD6OHopG0fDC1B0+jbVrwaoWk4GpppSYrnmy8UTjn3HAD2bV9FVfNvEcHJjDnuXlq+qoys71tYQqH/PZS5acwCFk1zQDjJKWTogB27veOpSxECux7iczWdz39vBknNu2Yoefn9ux2nBJRupjaEECTfNJpQqZf6j3YBUP7nFQT3roq02THqBM575/lDOTSdtt9VppYjO4bUm8egN4doXl6G4rYRKGwksLMeR99YXIPiUZw2at/Zjn9bLXtXbWJl9RfkLZvIef93L2B6Vz997M9UF+1n2fttsSkfnFaIZpPsa9zHt8XfMiljEoY0KG8uZ1LGJGyKFQZo8f1wyN+0t99+m7Vr17Jq1apO7+3ZY1447rvvPh599FFGjx7Na6+9xowZM9i8eTMDBw7stM6DDz7IH/7wh8MY+rFNg88Mboxzmxd5b10tr915K0Gfj/yzL0GPTsDl9nPCRRcx4cKL2FOzl6S4VEI2QWn5HpQ4Ban5KV21G3eUB9Vmi0iXt9YfqS4274K2VOxFbltFUowbu6JgF83YFRCKiipsGBjoVXVsX7aI6PiE1k4iY1WEQp0hafHEkJ/TF6e9669FKFyBtHRXBf6EaES4zoiitMYuCLyNZvZFi89HbVN9RJ9chDNJBILtVaWtWyY1oFPhNI2ZF5SbuPiRhUQPb0EYufgWVaE0g5YqkSqosXbsPzid4viPzWNLI/GynP16Jt74BPKqirm+fyYeIVClgS4l4/L6kxUbi2Ho4diJI7sA1ykevqmRNPhC7ZJhRActldaYjtbDHAn/PaB9ZNlBjCk1IZks2x7KNTcfKZJfHzf5kMZt6Dr2o+gBMmNiDDA0MHSQevjRAMW8gchwRdO0YTEANu8UyqI28KXxJBjR2DzbEYrKyTNfRjYGaaESGRuAJhVnQybMbdtUjC+ZWn8IuxC0hHRUQ6I2NhGqqTWzlew2hgzty7unlnHB/LZplD3rt5I5MLMtqFSCgoK3JcDXG/fQDGi6jhZsC0SWUprS94aCPcVt/uXFUvPiFoy6AN7cE/gkNpnUvFiuvvkCQrqBYWgIoXb6HFsF2NovF+E6Qq3bwte9F0uNthM7IwcAz+SMTu87B8YjHCqbH1oB1bBr1XLeuOcO+o0+jl2rV1BdtJ/Jl15JXWkJa6vX495Wz7PT/8H43Mn4dT/nfXwe539yfqS/AXEDOKXvKVw86GLSotPY37iffxX8ixOyTmBq5tRI1pqFxdHgkArLFRUVMW7cOObOnRuJ9TjppJMYPXo0jz/+OEuXLmXKlCncfffd/PnPf46sN3LkSGbOnMmDDz7Yqc+uPB/Z2dn/sYXlNN3gya938sy3u9EMyZC0GCb2T8Lx3v04g91X3jwSPjqhlIaYnjM5fvRF9zEYAI/87H4mbVzDwOoKLj9jBoqqkpGbQ0pam+fjsZdeoalo/0GN6Zv0b6h1dc6uaU99yl2EXG21O1ID1axdeBGqA7xlTooWJHW5nkSiZUhCGZInx9zInLFm3IIwDH75/O96vb83s15b5bFMiyDR0cJP+5sGddDo2rMjESypzmVtXSb+A0rFt/2Iwv2K9q9luHaM+aeE8273R/VldsppHdYUHXppWxYR8JKSLH8xF1V0LKJmIJFSdHJu2AgihEEovE92xZyu6Pyrb5ML01Eix6dzOkhr3RjZ7XE297LjUJxxNxLXfy2Bur44YspJHDIbp6Mfp577EkZQp/R3Swmk7GfAHVchDYnu91G3dSP1H4Zw91KM+GHZwld6C4o08NkPzcCaYtvDQFtN2zjL9uOoryIrajBTUs8HoFzU87lzDQCVuocvQj3HWB0K49Uy/nXPVTiiDt8wfOyyc+gqbycldwBX/vmvKKrKqx8/SvVb3yLzU/i/35tibJurN/NawWvYFTvHpx3PezveY0v1FnSpkxqVSkVL23Ru/7j+/Or4XzE1s2sPtoUFHFphuUMyPj7++GMuuOCCDm53XdfDd78K27dvJy8vj9dff52rrmqbS7zsssuw2Wy88cYbR3XwxyL3fLSJN1cW8ouT88jtE82y3TWs2ldLZUUVx3s3ce6Z01AUQbC2kAmb7qMufSrOtL5ErXuDAoeD/WlDcSYPJjZpIFXFhbTMWU/GpHH0zx3W6YohkTTSwqdffUGTM5ZpP7gGf6gRR+Md+EU+Q/vPRBo6RVs34Zu7H1+N4IQf/Kh15UgfAMts0Zz+f7/s0H95WgbZ/3jGbCclTc0tPL10LcUxSfw2KxsjnBVimCVckRhICev3b6aotIHc4UnE9YluTRSJZJLohsJ7zWVM8pUwceiJKKFmYvZ9w2StDCo2QUs19D8Jf1EdetFW6mIHEJNzMhg6/tVvUO6PoyVpCrblq/C6Y1g/KJ+l0y5kcLSkv6/ZzGIwWjVPTBlwI5LdYtD2lY8IUOAKVvPjhj9R5hiIljq+w7EhbDggDZat2EmDEYNz/AWmvDjt9Cs69NuWcQNgprQokefedasw/C0knnlHmwR4+/a0LgvrgITb+FqaSGkpop+97Y5549pSAoaN5Fg7nn5xZnVYCXLfUrKMRfjj8tnX6MLjcZGVmRhx0UT0TVrNBCEwCj5hn2MI9kEz2i1vfTCfbN+8hixRRf7I0SBM7RTThaOAUAjpkr37i9lfsA8Ae/R5JPZXaSjOjYxZsbdw/i8Hkp5rxoPt++Mn6PGNaCefRo2mM3mMeae/Y2sldRXN6BJ0KdEMA2d1FYNDAZAG1QU2lroD+NMCvFtUwV6tcyDwxGFVGBU1OBoc5A3OIzY6lvgoB9mGQbTfj9rOM7HwvcdRNDMmKTt6MMdnnItfD9Iw3o4hJZqhs7pREoq2I5F4m7bgdJnenaSkM7DZzLT1uvpdBAPbsNuvxeGIpv1ptvV7VbuzHOnbzt0//zlxqYmdxn2wVO3ay2v3/IKhA0/gzD/9Gn+zF1e0p4PHpdnXxFM/uQwtw8M9j77bbV/lzeXcu+RebIqN8WnjOTXnVEqbS/nHhn+wpsI0wK4bcR1X5V+Fx+5hc/VmlpUto95fz+3H3U6UvesAY4v/Db6zqrYzZsxg06aO+gbXXnstQ4YM4c4776R///5kZGSwffv2Dm127NjBmWeeeSib+o+ixhtg8a5qlu+p5a2VhVxyXBZ3nGaeVC8cmwWAbkhU5dLIOpXrviBlbz1K31xyLn6ApcFlnLV/LdRWUty8kqwrytm4dRlz56wnZcJIJky6sNvtL/lqHckiih+Pn4ZhGHzz7W1Ui7HMGBQuRDYE3t56JU2uJsafd3GXfUwA1jz+GLaqapyvvs7WTz5nyFuvE7rg/EgbN/B/QEViMlOXLux2PKEXY3DWVHJK/6EMntC1EuS5bz9I6t5n0a98ENWmwOJfg69NBItxP8E3QSXhrR9wU1oNhusrLu9/DoMaDKJdOYz61QsEWpqZ9bs/w6ZifpmfysQJo7sdU2/46irgiT9ROPoXTDjrh922W75uJulRTs7+2Y8Pe1sAn/+yhMrQPn54xaEX6PMGNfKWbObBLU8zZK8N3XEJNuAHT07v0K76mQX0qSylavqjTDlx5kH17b/vJRLz+tL/qq7TpAGe+tP/kZicyqgfdz9dehww78m32LFDIrU0GorN5X3HVjL1wsm8/5cVfPr4Nk75aT0Dhk8gEBUiujQX5xs7iAbem7+f3CYdwyY47q5J2DpkdbQVWqy+ayFpmcmc+dPR3CANPti4gTWFFby9pM1dcv3EyVRXrKdgXgHXnXkhMVFJ7K2qZmR2ZuQC7dc0appbEO8ZRCWm0lJbQVHzdpobannqtCQSolxcl9WHywb358Rwv2vWvkh9/d8AMIxzOfWUH0W2uXbdc9TVvcbx454kNrbrWKTNX6/m/UVbIhL5h0tyXj/i3Ckoqjmt6PZ0DqKNdscQ7BuDDPYcrJwWncaLp3WMJcqOzWZc6jieWv8UL256kRc2vcALm16IvO/QXMT6+1BWWMvQ2olE70vHFe2g36g+jDk1B4fbiiOx6MwhfStiYmIYPryjvHV0dDRJSUmR5b/61a/4/e9/z6hRoxg9ejSvvvoq27Zt4/333z96o/43UxvSeL6ois3ljcwvqkWt8IEOIHFnRdOc4OBv6wu5aUQWjnBAm3pAkKIRY16UvQlD0LUAHm81FapKqq5Tm9SPLMBmN137eqjnE4Zq11Bi9vP652cTYyshxgE29YAgy9bb4R4w4uMINTczavRIcocMYvO0EyMS6K0n6eDTL9Nny+oe+0nO9rBrdSWOHlQb44veC48rvCDUYt45n/Ok+XrI2bTsX0ACcHJCPl817uTOvR9ATh9mtjTyEOCMisZz/iU8YSth0pHGM7T3BvSAbnT+LA+HUIMPevhYDcOgcuscyvd+QZO6DqloIBUEgnUyH6c2Eu/6Gay1pXS5ft3qb+lTaaZKGI64gx6XFAqyB+VZCE8kHYTD1NlUi03vx/RrBfv2luGJTWDiWZcDcOldbj56fC5z/lHHxEvmUBNVzlDM4OrGtGXo2hRiNInHL1n29R5OOL3rys4OoHWWTBEKl4wawyWj4ON1r6GF3DxxRT7TBw7ijQrzpunZp19CDQdOv+uKQk9IRFRX4gyZ3g6PYRBIy4Zac8qhyVtKv/1pLB7m4Nf7q/l4/jdck5vB2LFjiY0ZQnl5Oi5XGbo+G017BJvN/M4XFRXh8dCleF/kOLaWGTiEAovdIaXRljrTbaPD719VVG4efTOTMyaTHZPNvP3zaAo1MS1rGt/cU96hbTNBUvrGsn5uIau/2EdyTgz5U9IZOjUD1dIusQhz1E3S2267Db/fz+23305tbS2jRo1i7ty5DBhw8Pnvxyp1IY2/7C3nlZJ2ypwpboyUNvG0EPAhAagLELfTxo+HdA4UAyDsntTssQQCjYysKQRg+cjzGD7dzCByhguChYL+Hsc15Xxz/r/Kl021cQrCNYALJl7XoY2iiN5sD4TDAeEURpfLxbiTOs/vbvxqDRSs67EfZ5RpNPVUuqUp9VSce3a3LTB0SB0GY6+OLNI0c78nDb2Ua4ZfwZvL/sJDu96g0J0baRMRDTtiWk/cvRhouoFyFCqxCqeCorefvgzhrdlOwFtFsLGKkpJ38LrXYyeZmNBY7CIehEQKg5MVySuVLxBsysGVcAcgufz6aCoWzyN6wAj0sq0kfH4eNXo/gmc8RdqEKQc9LgMF0VvNHdG78RH0eqmocpGe3EjehLPIm9Dx/djEZC6/+3w+efoDlr2dTvLILXx66hcMFqbXtJmvOEd7hNeXNdPvmzKCyQ2g2vGv3oTh13D2T0RvCmEnGUPvrNWhCBiY1czMfDOmaI0OsUCTJ5qoxFTsUVEEiouQfj8kJpMzeAieKBeVW1ejF7QZ18KWxvSNXq4a1ML6pYsAWFFRxIoVKwDo0yePofllCDEuYngAREeZKeyqrftTbKTGkXY0jA+JovT8vSymLzahkTvvKwQGCgYKklynxg19++NWBSPjUsj2dG3QqorK8WnHAxBjjOafizbyprYKj1rF2Pp1ZB93EsNGjyBpkxOCGhmZUdSXt0BlM/Ff7qXsy724Rybj6BuDZ1IG4t+QNWZx7HDExse3337badldd93VQefjv4GtXh8z1+7EkJKfZvVhcLSLqzP60BQM4dckmjQwhUcl66uauKGwlG/21+I2RCSUr1UoE0CvruEyI4OYvXtobqxjV/NVbBuRSVLONFbvKUVVK6hvrMJtz0TbVkexe4PpCVEVFEWYdUpUpcMP+Ozj/oLN5kAIlVD9jvBcvA2hKEgjgK5JKqqLURQVVVFRhBJ21arYVBs6ErthoPkbkVJDSj38aCCljlBsZl0UQ0fTdIQUZgyHbhAMBM2gR93A52sBoeOrbqG5Mlx7pH38gBD4RQ5S2hGGDg2FZtZERscCX8GQua7dEUWpv4GH989ncOUJ5FadxIt3fESgJQqw8yuOgnJu6/x4LxdV3TBQbYdXAK09MsrA0Lxsnf9HGgIrabHtQaptgdeqPYa86PvInnZlJB3UMAy89dW4PDHE/G449mgfKfYdXJJ0J4TV1rW5DmzCvIvn0tdIH3Fo0zoS0avxIRA9WpbLX1vImqUa0I+Tp7QZBkG/1sEb5nRHcfHtP2DOa2+zZ8UlBJc+gnGNQLFJovHSZBc8MtTFHzd54d2W8Lb7IJQQ3qI4QGc/OitqKjmniz3R201njMtK48F+9/H4ae8yI30ohm4Q1HSCIYNA0CCkaTT7gnxti6dZq2/rxWjk0rQ/0GfpfjZpN6Pb7MTgJYidAE4cTh+aNo5TT3mlw9bj4uJpbGr3ve/qOB5lz0dP9X0ARPi7PczlRwd0KQgYBgWBeG7ebd50qNomTo31clveGEYn5XTZz9J9e7j1jV0gwx61mD6sO+dkCGetmRKugkeLv2a8dzQy1OaF9W2swrexCntqFK68g68XZPHfhzUZ1wvL6r08vKeM5Q3NJDtsvDAsl4nxbT+mGIedmAOuRT5dh0L4dlM5i77pOjsklmZO4knsW10EgER1AMZKjW1L24tauMBzGVl7VShu7NZLHzNiPE3pK1lRcEW3+xHQU2ipSuJfN/2s2zYDy2oZ6G1h5+gJ3bapSJ/K9mlPsODmBZFlEokvupjmmHYCSKkg5hvUfd1dANpISnmNtGAAdoXzKgfMQBo6DbtWEj9wIsv2zWMgEBQKL239AhkqY3Dtr8loVMBdjjs6gK/ZvEszgt2f5L0BjTP/+DVNmt5BMT2ExI7gtR+OY2hm611jL8aHLlHtR258BJylBJ1llGsb8QRHkSF+SFziaKJis7BFxeBKTUW1OTus89wt88kUKtkOhSfoi0gEm6jr0CZieACxn/yE0Cfh/WqN+I380fa8XaCsR3qpaGnroytCqkGpKGTpF/0gnNkSSY4REOzjIu8cJwhJEVD4+X1Iw4ahOanbOYOGfZOxueuwR9USaMjECJlTkA7Pr9gRFtXy1/2VX2FqVswGFiRNZWfsYHO8BkiqAYkfJ6d593Pfffehy9Z8IrgAoELnnj/cY6Z4S7jKuJyUvxezT1Zj6+JjdgNnZ9/A0spPcKavZpixkzznosj718R+RmpLGR/sHUq5PxaHQyFY7mPfFpWX554TCbwVQkELNWKPTmfC8d2n6mgB07O394VFVGKn08Rf+KN5FJVauwMUpV0pgfYBrHCqUc/GjXOpui6cBdXFz2Fgg2mcPD31rx2W1wW8fFWxl/mlm/jEl8/sliRmb6wFajlt5xek+GsRiplUoKgK80qzQOYCYFcl2BrQ1PRO56dFmc2kZ95MctNFDDj9t9hcMZQ/sgolxoEz9+CnAi3+O7GMjx6YV9PIjzbtYVRMFH8dnM3FaQk4DkIm3u00tT2mT83h0pSEiCpma/qhFIL6YAhe3kXdIIWEHeadjyYlx1/bB1eMC83QCTWFWP1qNbK/B9eUeLRAEGkYGLph1ncxDKQhSV5wNkmlGcSf0RekEc7w0JGEH6VBXOo7eIP1VE+4FSkN825LSgzDbC8NgyW75jC/RuFnw09GkQqqML0iqlBRpIKuN1G2MR98MHhiGooCUgq2rSnEFormhONOQwhBfU0VG/eupSXLhbtvWAb8gJO9LNiKoy6Wp/7yABeKj8gGqj75LcnvXUM8UKWmc41eBsAXb87HVd3ElXV9iYk1j7+/xUzDbXVY3LDoUeTm9eE7zY6JqhINmRtFZsUvGJmUgyJMUapqb4B5VQ1c+Noq4mQzG9wQaO584S15/c+493yEXTaha5mEQkc+b63GCkSji5NmbDjoGh6xySp5XhWXgBpF4op2gkhjt+9ukuJLcLoMlJZdCBnAiMpDENbfiByoVu9Ta5XhdgIsCLRAiDVN8UhlPD1NkhoOO9hcpHgmRD5XEc7wab3Tr66PRY/pG95WCF0LUF2+g/TjXyX9+FcjfbVUDkKpfYiN23YSG+w+4yPLGeSCEc3t9sVkjzdEVU0sBBpJHHgcQjG9cc2hZtxR9UQ5DXRDh2qd6pI6Coe4caakIlSBalMQdgWbqqDaFGw2hbR3dnP6jDHEXfkoABv/NpBAfDZun53hlcsBqA1GYbcZ5J04iKAvQNAXMLVCWn97GARbFGq3axha96fYwnBxv+ZAA1ExfcJGXMekbZ8h+TZgZ4QwyI12R3a/vXYMwJg+pdSF4nDHt5syOcCLVxATR8OQIZ3GkeD0cFnOCC7LGUHq4lU8H2oTIIxWo4jCjwyFs8cMiRY0A2hPG1hDQA+SmF1HKFTCgtLXI+tleg0uHWoaV1UxH7D+zTJSN05BuPpilIYof+Bj4i+8EPeIEd0eH4v/bizjoxsKvD6u27yXU5JieWFYv0NStQyGf/QDkz3M7N91pHtpsx8DaGysIwHzLsCQEKoWDB2YTUyim0BTgNVU40yJpc/o7i8HNWs2YfjGkDSie6nkbWvmkeIuZNwpP0JiENADeENe4p2xxDpjUITCYwtGU2ok8XY3fahoqDmSxHrBmvMGReazdxTswS2jmHGOKXxVVLCXjXvXkjQhjX7julaY3K7U4FjkZ2hOGnW+CaTXzCI52OYlStbLqHFmscOeToM3HuFRqBk5mphqLzEhB4lJpsGmGxo7/BKPazfCiGVEyhlt6anhO/uaQBG7fAu5cUo8F5w8PrINwzB4+dMdVNb7MFrqoRKy7Z0lufvsfga/7qE+5TTqt+7B3tS7JHdveJu3oxuuQyoeduXvT6b4LvNO/PiHTmz3zsQjHo/mD/HiX/5ONX25dvIpPbaVisDuTifvxIe6bdPVpy4NScGaT2lpLiE6NoN9hY/gjG1gj1qAe3MCz066FYAfNjTyy5r6yHr7ZTq5f/y82209/9HXlG4o5sZLT8fVjaT63hXbeG3/6+T1i2LAhFxUu62tOvTWPVRu3c3Q82ZQ8s5uqGskuHoFEhsDT/yQQFwVzqRUqjUXSUn9iPnJWfTtm8zJ1/21y20BfPXW62z6+J1uFVQBXHFmXEjGD8Yw5LhxXbapbfDCgws4e7idGy49scs2AOX31bM360Qm/fRv3bZ5dfYHOI2eY6QkoBg6pTOOMxecPLpTm6R3n+DJtXlsKpVUKZW4nW9F3rPr6Vw1+Hr2zX+XtNs30nTRAPQRtdjKJKi5QDTCYVD//qfUv/U2A5ctxZZgTb/8L2IZH93wfFEVAP/Izz1kOe1gawG2HlaTmmmgOMaNwAg2oHzVgFsRrP+sivWfVaFGa1x5V6uKZc9TAWYiS88XsWt2/8p88vuvu22j9fdAWIQ2Xzai17VwYjakxwgMKQkZBl9uc7IxKYm/3zoPW1hAC92Js09bhoQRDM8fO7r/epWWVzKQWCaefQ2xqeZFp6GogLK1s0nPn0Rs/+NJUm1MAhbc9zti4pP4/Q23dNvf/GcfJk0k89y5v+r03ubSrVwxd2En5VZFUbh8Wi6bFpag2RX2FR6Hy945aE+VQRr6X03OtffA4rOpLt/dqc2hogVtVIb6cNajLwEyonzZ6pVRhURVZPh1+FGR2MnhnD4+so54BB355t3ZVBuNXDhpJn1HdZ1ZEkEaCA596kkogmHHn4emhfj22+E4YzX0ljz0r1MJemr5ecYdtCTUsXbPPETtEgIyneXKFD4ODqT7S2pbJlZP4Tr7Fi7Hs3MDn+/cAE+ZyzzOBBw2N7XNpuKuJ1ZBxaCpeDhN7weBIC0Jayg6/mEoDHcUBCUvhWBzfI/7KsPnANFDEKgnoQ8A9qjutTFC4SKMvWVYmZNNvcV89Pg2AFXV1YiYrgNOWxmTUspz05/htFO38cnaT/jdZrhp8KlcP+GxyGexX3rwvvlLRNMAJp37KcoFKkZIp+mbtVQ//VcItRA1aaJlePwPYxkfBxAyJE8XVvB2eS0nxHko9/rpG+M6pKq8xX7zQrzd20OWSrhSp1QFMQPSaaaBuOEtpGSlsmlWHXqzjVf/sBiBo/e0RhUwej459XPVsNefxFXTDJSwzLjb5qYp4GPxDi9C9VG5u4Xrlr7J05f8kIKoWEiMZdjOWv50ZZt+RH3JIjYCSUNtOGmLJ8if2CadH9hvymvLQPeBdFEx5l1fa4VbgLjsfOKyO5d3l1L2Gkx3oIx1ezTNNIZsauev+9evbqV4mxk3sZF7mVZfSxpg6BpSQvWqpaSKACKsnCkUFxmDj1zlsTo4lHq/pKA6jZP6VUYE0Qwp0aXEkGAYgpAhMKT5p0vYRYh4EcX5RzyCjmgB8444Krp3kShNA3sPhmVvKEJFKBoYULjlTJz+OuJP93HemDPw1VVzfr9xbF/dxP7BTawM9GN5cc9KuUprPaEegmAbFfNmIn/8aSTHZ6C1+GmsqSQU8pPlymfj5nl88/b7XH7rjxAhA+xRCEKU7TcDXYe6rwTRwlY+wpPewtDBl/HNxzeh2jT6DryY2MRcEpLbfgNtxkf339uIWnkP49YP0vhQerlBCW+o11zyQCAAvZRCMowt2GwaQgjOP+58/rL1d+xt2Nvh9xc3cjxfTXqAYFMsq29aQGKolPHT4hHvv4BWXEzOKy8TPWnSQYzZ4r8Vy/g4gOwFGyLPFzV4mbR2B8frCh9PH27WLzmIOhxx4Xr1me6u7w6lYSADZmyB6g3SVONHAZIy4hl1+mgmnw7P3joPRTPX9wXMmipBv4bd2bmGhAjHXvTEtKQgzopy7j/zJ53fPAuKWwIsvehqhu/dTGn2lcwbrVGWaOPDjET+VF9JUnguOTkpDpoMzvjRJJLDFXE74Qxrmzi7/3olJSUCDQd1N2ZW/+zF+ECaAX9doIV1UmxdeDVaT8aX/noY7/5lC0Lzsuu+48ljBwCpgE8mEDvOnIoQiqNXQ+hg2FPnxkMz2/54Ci6Hs/cVwpxy7xzstm6O+yHQOn9PSGJoOitKzO+9muigsqy0fUPzMawTIwBNU3B0U//nYFBUBZv/KqI/fIspi58zFy6HIsySDEpcNkpsBkMvvYvNi+vwGgaFOws7jEe2Sx3zNnjxq352V+wm2uXEpthQUCIZXTbFRuygAbByAYPOnM6A/OEciPPxaFYt+4TVXxcw5bZr28Ya3AMNkJh/C664Pix7aR5xuU1srb8LNUbDELCrZB76XoUZp25BVVvTzA0zxquH80WkCGMPv4HyRvMGZldDzxkxydQSaljRY5vwVnt8Nz09A9FzvDGwFYAHFt7M23vNwPNZ5btIXnQjJ/c7jzGZp9Pk9xN0xJKQVIe9xUYlGcxeChPtaQx/51GcXdT5svjfwjI+DiDNISgPmmeD8+T7fCIuZpVqkLlgIwDxso5H+QVufJF1dmyfRHHVYBBh56eUXKPaGBm1Dq93IYqUKBioUkeVZm59n1Ae1TxO6tdlkX6WrV7OZ2vNzA8l0YnLl4Yi7bRsqaf4rqZIlkZ4siOCSn/qg1W8c8WZZu0QAUJIFEyXvRCwP28s27Up5N/7vvmeCNcaCbv06/wxDMo5mT9UlZNbpXHl0gr+NjMFXdg5aeFWooLrEVKyr48pBPXEU0/h1sMX9eoybA21Ee9Qg64yN+FElr5VgPP9XZGia62hjQoCI6ARh+Avwe5PqsV7dvHO668RhG41AYKlXgyfFjY+evZ82NtpLughncKttdQUewHwxJvBfLatH5Dn3kHQcFESHEHcObeTMOFU3JH0WkHpjpU8+7M7Wl/SumdtcuWtMuqty82dF0IxFciFwgBfBV6b55AMDzA/9221LTz32npsikA1DOLq93OSaEaGNGRQYoRAagrScKCH3BjEAd27/4NoENZoe/Xd3ksggJOm8prem/XACSffxfY7Ost8e2Y+GfEy8X4VlwKjiebElzZ1attKumcD3pxZzPp2VrdtkuodnEM6dc3VXb7vDktBZ47pGAApwwG7ijCP39ARt7Nv/3O4nJkMH3w3W4u3sHDXLDaW5HPXgs/IsPkRWoBgYwPRCRP4eQ9ey8j3tYc2ariJu6c5XMCnjye6No+G5//VIaFJturyC4mWksyuqDjunbe1Y0FE2n6fqwMS7JK5r34aDjY3mLLvJurSJuNLGAiqg6iKbOwxe3lbW9BhDK/uWcQ/9yzmD0PXg5YK9CX59AymT5rAc7d8i5SQ94/HcKYcvSrTFv+5WMZHOwxD46WYl/i2upRybTLD7ZmMdmykJTqR+tpPkAiiacKNjwbPqQSbPSTLjxg0eBnBlJOwB/eh6I3IYACtJUi8LY6Ng28DoYKimDoZQoBiw1O8G9c776LEuGiyJbEtOR89mML4SWPDdTwkIb9OaHMtNVmZ+PISqChsotQboCZWRVdEpHhZduluEncuZMqJI9uyYaTEMHQMw7zDjcufR3JFNYmJJ2G0uvXDqXyGlGys28xKdTJXnTqJmMb/I39HDn8oiGJjwlRcIiNyPhuyYSW1sR6S3S5UVUVKiW/XZmhpIiZvKCDZ1uCmxJHGIIdCP48LTUoW1HuZHBsdiYNZpYVYp+vUqNDdDPP2TZtokgqxDoVxEzu7aH2bq6n5l3kXJjMMRFTXJ+hQWIjMVxdi+Se7Kd/dQMmO+sj7CenRKC7T+CiNvYBd0ZdSVpfE8efn0W/ioA599Rs7g4o922l3dg+/Yx5Mc4pM75Daat7ZGuEyMmaWkV31EOPuJbaiCwbHuvmmtomCghJTqwEAO++jkOO0I2wGwg5qtMBoaSIUygQCOAcmIlQVFIFQBajhR0UQrQquD11CObXM/fIf5PQfRfro1qwIYRp27XRaVn7yFs74qkMe+4F485wE3QLjmj9HLsS79wcYXeSioa+H7EGJVH+0mL6OJJ6dYk4HiVZjr91HHQiM4p7AOwD8ZsjdGEh0QzerORs6hjSoLSsC1tKo13c5loC3GYfiou+Jxx3wjnmKNDCnUvPH/5DEYWfx8YYCfvxUGZAIXI1DhAgZNmpDYcMpxjTS61qCRHUX09G+um03JESZAbQ5MT0LiJVpt+KQDtR9PszpFfO7F06ERiIYozrZ63IyJ+QPL+v8p6GSXV/L2r2bMZDYZICTRQOpJV9ilMw2RckAyuGR6CBpmkasYdA/pLHXbuO8zHR+v/UNPIEEruI+ooNNqHaF/OPi2LK6gX/9biW5GRozf9dWUFGGQtSVLaOucSUOPYuYwBjixg2yRMj+y7GMj3aUlLxBffUXXDH0ITLSL2bv0pdxrL2bt8vO4HXdrK3yk+GvQQZMSbyQ1PGnMeuLnbhcmxme0Llib476QwZO61psLbhxIbv/fAOvTldQSCTTN56BrgbOuuTkSJuaGh9vL11G/MgULj6xX7fjfuCFDVTsrOW4G//RbZtvPr+EU7MXcOqpL3b5/ldfjuTG2g/I+l0jQzYVdBul/+mzz7K2cAc/+MlPSM7Oxudt4pnFc0Ao/PSBRwDY8/pC2NLEby8cxKDkFCY9uRADmJQeR4uQuJ02JiVG87uvK3D1EDtghE/KP77x58Qn9en0vndZ2/RAk8OLEQx0eF83dFbMfY09/1rDz6KfYOcyP2Bm1Kg2hUETUplwXn+iY534W8yLi8idzMwrO6cjtnL+L4+spksrD923BL2xV/92J575dceMh2VLvuWKz5rp89PRpOS1VVvVS/dQ/vedKEo96fedgegmC6SVBCBdSr55/2Hy+vTl+LPP67bthveeISb6yCq7Km43W357Cg7fen5wUlvdJ0M3WPLXlWQWeglenY/yyg7U5HGclOxFX/4v1FFn4zr9px36eu+9PwIwoMbO5cdf3uW02JLVX7CctURHdZ2pFPIHulyuhKdQm8v34IpN4ZOizdy2y0ug1B4JuZ0yOp71pQEC1T7EAY48padpFw7C8xE2HubsqmPfWwsiXorc5FiumjEm0q6JWMr7eTj9hrHd9AR3hf8OiotN40CGNHjgCQKjHsJ5wY1IXcPQAkitmVM0H1LzYeg+AqEW0jUfC7UgPh2q9u5j0VrIcZhThHWffIIvbzABVzUF9VGMufMunEMGE9xfSP0HH1D+p2aMcB2ylK1XYldvIvq41IMdrcV/IJbx0Y4dO82T2M41D7FTeQTNVc2Mai+/tL/P38PGx5q6JCZngF01dSbOPOMjdu36guLiL5HSybhxv0Jv3su6bVeTFNv93LwMmhee6IBK0NZAQuMu9hm57P92M5kTB2Nz2QmGg806FtXqAl1D7yKYsj1CRqP7u89QUJtDOApsCEP0mB7YWgHUHk5JdYVlpOP7taUCj0m28ybw9ZJSbijcRuv5+I9bSyJtzk41x/v13K9IiDKft6qlFjcGiYpPwVdiGhfdxXIk/mAo9Sv2sPvFP/LKxzqwnXnvj8OXGkfs9kpSGjQSgP5Jw9kY9qanOmrx2ANIILCuhIXr1gJmzRZIh+ambvf9qHKUbuoMI5xZdIDku/f9uUiZT/Llyb0aHpEhCYFA6TFwE8wpMCGP/NQhhIqg47YUVaE+1UWcVyPLZceRW45Xk7jmm7FKxuJv8M39E3a7F38oA9vP3uSPLe8R0wIPz/hrt/E4Ad38vTnVrqe59mxdjScqsdPU3bW1QTaKDzihZBG26hK+CQxgqCjCyLRRVu8iWGSwZH29uT9AUt8YJg7ow2fLC009tJ5+uq2ejx6CRW1SwyMCLKu2s6w6HMiNQOKlqtFnTpcIwTQp0fXuBc0Om9bjGZ5+EqoNVbWBs+tzmwuIB5Sm9Uiq+HLBPrIrDUpGZ+NVdwIQctYxq6iaYc8tIKG+HnvfvujrAvw08H8AJCsh3ntvO/Y0A0dm14UpLf7zsYwPwGhpofTuB7GNBxEUOAsawOZCTchnd205m5vd/KLqeeKD9eTsrYdhIP1mzIeiKAwadDaDBp0NwL7ZD7DP9xrEgVHdfbaL0WRe5CbXTCG2aAd9fhbP3OV+Pn+7EuWNYpz4cTl0IAFbL7n5aCGMXowPk65Pck0Fr0JikODJAfrsDtD8tyvQQ80EKxT8gWxQFGxpqaTcdRfJbtOtXLpvH7EpKSiKgojy4K2pZtFbrzL5/AvZM+9jsJ3IPwsbmRYTxcM/PZ4lK4tJSfMwNj+F4/80l28qzX3avWsHTtH5pNlUsgsAEQqgdXNuVqPt1BXMIWataUCUDUnBH2vHUdtESoPZf21aMiNffoLCPy8gJG20hAxa2n3tI25pCTH+fXhqnMDxB3Esj4yj5VDWwhcctV1Kp2yqo6l0MM6YUhyjLjuk/hShous9f98U1axFc+QoXd71J5T5KMl0M9Km4EsaBBXgm/A3nMefiv/FGxBGIehNeDyFNP3zROL6p5OsJjF41EndbikiZa53bVg1tlQxYcpFnZYni34goVLtT0PAzo/j9nP/6PNRFDsFw5v44TvruHpiX/pEO1hWVMcvx+eSGxfFiGSD++o1lB6mDiq2bSFm62pmPbSe9YOHoqgq/ccez5gzzmnLrtNDXOzcyPgR+Zx1kVkV+61vN3D37GKeWNGmbjsNDyG/t9ttHTZK796Zrmio1WhIKCCk11GyeSeo4CKOG68+lzmvv8729DTiAgESVq+m3/vvkSoN+PNiAKoMO5VIQlf/CufAaPS6erSqKtB1PCedhHvkCKInT8ae0U3dLIv/CP7njY/m5SuoePhhgnv3krVnEsIVS2DTN4AG9hKM1H6MysglPyaEJBs9poxS1oPW3GV/VVVz0TM1Yt9TcZ0a3+12/bv2ATDilH40n/gn+o3swxUzSihdVkDF9hq8tQHqmwRxgRriqnToSXNS15FqL8XOesgW2bP5HujjxBEySBjWjK3hC/ONGNg6K53WS6XR3IzP5cAeDPLu7NkwezYYBi7Vjq2hjpUfv0fV0g9RKg0uibVz/czJOGxV6OsWcN6p01HsDhYu3EsLkKwoNOsGt916K6mJsZGx3PXwU7h81dx59z28/+EXVH78AkYP+gVGmVlRM/m5Zxk6bVpkeUlxCSufeY6zf38vdqeDK1/sXnoewN/Qwt4Jx6Eef3fPx/EYo/Vu12YzvRt6eQV1r8wBcoi/YnwPa3aNIhSMXor1CUVgaEfB+BCik+dDMwz6NGk0D4o3m8SmQaWK+0xzuivqri8ibYObFxP11tk8UVHNLalg+Hwo7m7q/LReO7v4Ku37aiUGBtFJnTUnZrhS+drXwLeTz0Qc4IHM7xPDqpvapsF+MKTtLl2JVHTqnqRss3aK1DVKtm5GSknhpvUsevNVbvuXqTPf4jNvcuoa2jxyV5w0igsm56MbMpJVU/fHFajRR79irBACKUUk8PZgSelrejgG9Mlm9MQTKCuuIKdfBnEDBnDpffdx3333UZA3gCaHnUEOBzFOJ/semklLUzNaQzPBOasIKP0w6mpwDszDkZNDqKSEhs8+o/6990BKsp5+ipgZM476Plt8P/xPGh9VTQEW/P2fDHvt8ciygMPFnoAPGfQjcvJRpGFOZQiBrCqKyKI7kmtRgXWVN9PyaR42mwoo4euzQpS7CEeBjaSaK/Eu9xHc+6p53RcC0dpUFWiVKq7jbyC4W8HVOJ+yWQCCOCGIi3KDx02zz8eW8hoeCeq8tnFPJCLd3FKbvHKDoZJjd7L4T7/vsJ/tg/ManFsYmNxI1ZdXhgvE2RDCBooduybJKPUxdFczG8ZcQt76D4gOu97lbbeh2O3Ix/7KH3arpKhehhduxTshGx8KUgiMhHhiohTqKmrYW6mT4dK5MP5EnMvdSBGFlCrl365GczRxZzjM4fTBDv5V4EcabSe1tdv3obTU0eRINGNBGs2Mit3v/Itypx09pGFoIQxdx9A0DE2jubyYDKD5k28JLdwc3l2BKmCSJ52ax14CQG/wI9y2Dm719heGyJz/od3gHT5BL6EQvP7uu6iKwKaY8QG2cA0Nm6qgKKop/a2qqKqZOmo+N//w+di5bgswFKGZF6nKZ9aiB/uROM2LrV9uh02ueuVdynZuN4+driN1U2bfkLoZqCwNNCPUq+dDDwr2rS3kuVvOxoyfleajGUuLNEDTJJ6RLcQODiDaZVYBkefV9Zn8c+uN3L1gduSLnWUI3tKiGLaimj0rFqKSiZ1GfL/PCNsNZv0WpKBFTSdqxlMMm38z/yyrJORrwul2o+kal71xGUVaUaTfhHqV00ji64f/xjfi7xhSmgUVcaMHqol3pGLfGEvB+oVE2RXs4WBcf6oKQ538aM4mSh2CUIwdhybJC0CaomITAocisCsCh6LgUAV2RaGgMQSKWWiyO1we0+g+81e/I3/ceJpqq3n+xh9htJs+iQobUxkpHZWSD1RybUAhYS80LSs1p8XapZcZAR3hUDsGcB4YuCvC2dSGpKmlFuFSTa+mqtBHSGRtAc171qLYneBwodicKHYXisOJYnMhbB3Ho0nzOzR+bBqDxw1ixLiOgdvDJWwWUJSTg0FbLlZUTDTERMNPZgIzOx0zKSVGczM7xh1PzUsv4x471hIq+w/lf874qGj0M+OxBfQtCfIoELI72TfIDNwyM9LCqWnhq1Dr69Z52WpvNqkU0tyUSEjztxX/Cmc3iDoHno3JOPqfTAg/SlOlqcEhFZAKMvyn67nYw2VPtJpmIgm0kSwJcDqSGRuXQ7Rw8lVNY7f7JEZOZWfGALLff7p1Sac2UwfWk+9tQu77vJPWUCJQGG1n2Qm/oHLD64xqN+cvHn8CCfhVO3NywwXnsk/i53ueQ20XXdfqAD5h2ghGDj2F6jkOdHsz2b+dQcXKbwiU1KAIJxm7mqloTOTDHbVE2YD/Z++8w+Oozv3/OTM729W7ZMty771gbMCmmh56INTQQwop5IaEmkJJgBQgIRBqgNC7AWMb3AB34265SrJ6r9tmZ+b8/pjVSrK1K5Pcm3t/T/x9ntWuds7OnJk5c8573vN+v6/VhB3uCG9+9BmmcPCzW65FCIFZatObv1ixKOG5F5qpFGpegove4vDE6v1digRucCkxFQ3Uf09HltpVRoc1jF9ucmEkfQxtDkJijEWxTN5dt4ip4TbydZvG2LTCT+eaNYz/ZQ9LaP3StxFCwe/JtLMZK7EBRiioqoamKAwdNIWRJ8xNWncr6kCokszBGQhFiScdE4pAxLIu7/qyhtrqXFImD8XqTvgmBXEOhhR83pBPZySFmdNy6W7ziiV5uc1iuOZAtaC2ug6vvpWRqVcwJCPm1ZASR+MW8sPLsY6/hO1Ny5i0802Cmj1oH6w/yB65h8EMZkL6BAQCK8UgGO5kCEV0tXfS3m632LyMETjDIxiaNR3p8tNS3YXmc+BOcSJNybSwxUmtFltdUOtQUEMRLAn7LUmKLjEERIXAUCAqIKrYkxQUcJkSZxIq+aGZlA9sXAdAyZRph5U5UpHD9vf+dfXdQ2G5vHhqXoO/v5a4jAQLFQsnFg4OMhzEibyyeD3uJXtQFQeqYmfPVlUHjrThaO3lRIWJ2k9Kg0QQQqD6/Qx6/DGqb/sp+089jZTTF+CbOZOU009HcX096vpR/O/hP874WLmnka6IwV9+ey1Dsr4PxDJAHyE+WVzGzjf20Jy7hlx/Mbf89NuHlambW4nx93Lk+UPIPebUfvfTtaaWtnf3kXbOMFLmFvVbprqhC/n7r/hZSSHHzEosqH3drx5h3+ASfvTGRwnLBH53PtGWZrQHe+kc2NxPXv/DIC7pDFC86jHaFYUtLieTYyJogz9fhWmaGNEo3sfXYwgVXarc/OhjeLxe2+1rmUjLNs882UW0Ln0dKMBK70BxahQc10Orm/LWi3y1HnK8Tdwy+Rmcjrfj26yOelzZReRm2APokGGTGf/ZZxQ893dSs9JRnU5UpwvF6UR1OhGaRvt7XxBYC9nXDME9JubG7jYg7SQvdK2poX1hGVnXjMczpv/kZV2NQV64aw0nlwxJeA3/OzEqSyOvrZr77r8akFimiWlZmKaJaRoYhoHV37tp2mWMKPuuvQ1TKPiiYZZnzuWpaBNnD8vmugM6CuAN910asaTFpOmncMKPr++3TkcKgUpaTj4X//QvCcts2HADmlbEpSffm7DMu/u+QFXaeeOSxAyNO/6yjpcPTmXjdSeRld6zpFLz1hOwbTkd9x9DidUFAn7w0UV0oaN3WOCEtmgj38o7h0mz5/YZvJsbWnnsL39ixrjjOfuSHrd9e2UHy+/bQN6CQvJPLwGgAJiqGwxftY2SgMXK0yZz5tJtjBEOHj+jRxNESmln2zUtolGLnSt24P2iC/f4gXU+ulldE08+naVP/4WKLZtY/NTjjDxmDmqMAp4sKBXgDddqJqaNYO7p8+zSFiAlVsig7e19uEak4Z2Rf/gP40xx+0Pd0h24WjSUb2TY8TGWRW3oWRS1AWnpSFNHGPa7NHQwo2Dq7FqxBIcjh5Ez5yINnVQ9SlGbheUejpTCbtOxV1gPY0kDaTrQzJQjEm48FCmnnMKIzz6l5dln6VqxkvY338L3wUKKn/7b197XUfzv4D/O+FhzoIWh2T6GZP1zKpGtNQ00560GIDe3n4cZ4pKFyVgjwm07GhV34lsQ5/8P8GwqQ4eiORIzWRJXwva1XvyjKqLRThrf+Bm5+15n1E8OElUUNMWBv1cg4+jMTXzVYv/vTM1C8/YvFtTgX0LHhBBDj7nosG13nX853z21hcoDtbS0tNLtcN1xsAEsE6+vhwrpbG/DH4mSMmo0qf7+1/Jl1ARURC/FTdF7fQoRp7QKLfH9kDG5+3+XtoAuHLQrTtaUfoFD2A9i73fNluIgO2c47vTDDSIZjWJ19AjU3V7+LN/78h9M/uH7PDHCyYoKDVdpX1lyS1ooAzGnjgDJ1GR7IAYMUuwWzEuGunY7aNtzCJsnbdYZVFduAMsgGAyyszWHjugeOq1Oml0WSEGnO8zyF37J0ke9XPSr31EyyqZQ1x60DfCiwX2ZFHp7jBHj7zsTbw7qGIrgjoIsnE61XzNACAEqCFXF5VRJcam4TZIu4x0qMhaN2OdqmSbbPl3Etk9tj59P1WjNK6B2T6Vt4BCL9YjpyqiKSrsIYqYreMZl9TmG0WrvU/E58U1JnrMFILppM2oTlBzbWwV2yoC/W7gyhMDLidfcFf9uIBWb9+77G5sjdXzyhz+hqgJFUWNLRgqKqlCmOxDubIYUZjH/rMNTGjgyM8m97TZyb7uNiiuvIvD55zQ98QRZN9yAcPzHDW3/3+E/7g5trWpjzvCsgQsmgG+oE8ph2pSTOfuc/t3T8Yj62GxLN3X2VpRSXraH42acTFrakbn2G3WDHGBPKMwxyQoK0aMZkADu8EZUd/9BgkJR0FxpGFoaJgoeZ/8D/dSSbL5qaY39JnGAa5ZvHFWFj+NLvfWwbYqi0L6/i87W3QD8+ZVFdLR34dNbcQvwuHqMKO+alfaHJMG00jAAFTQHpiW59vn1tIWiFGd6eewyezlNr4wF6yUxLKIR22Ufjf4P0BX7wTZHLs1uHz+vT54hd/a+tbx7xvmHfR9Yuy7+OaU4iDdPpyknE4RgenUVQhnap0XYA5WJ8jVc3AkhZVLDGrBjpQYyPo4gvmZbZ5DRThdef1/j2je4BN8P7Xie7au/ZOMLYf5yymDSswazdvmt7Gv9ioyMZpRTa9j9xjDevPd2Ztz4Q1JTU1m/rBSAVa/uY8yUUaxcU8X+0haC+zrwAMLTt1tsD9vLXikxA7dVkWQeEbssOQ6d8Wsud/zzrPMuxun2sH/DOmr3lbJj70621Nceuou+v9cOn4DIWN3N1iR5pnqXlwN7WfpHbNn4a6DWpSOjJutbmlGkHTjbrRJtxoyHpbqbqv0O/ti5BL/Pg6YKVIeKqgg0hy2fr6iC0DXfQ6m6C/70KEpqKpmXX/5PnMNR/DvxH2V8VLeF2N/YxQ3H95/m/UjQ3lIPQPHY4oQdcHdSqe7tJ975EdVS43RSCS5fwsW/vuSIuJbu2GCZOgCTRQEGSO2CFB6gPWmZSCRMsop9+6QJPLvJTumeXDwpeX13lH4PX94uTNOB2XgQhzuL7LGzOXbCcCaP7hFTC8w5Efe+UjuTWaIsqkYsgZdL4+HFu1mxx1be3FLZFjc+nENS0cs6UFyJ6xWKeUeaGkIJy/x3wnBn4Y1E+HxMCoYEQ8rYC/sFPL9rC6Wif++Sb9ZM8n50Mz8K/QOXO8q9OQ/RVKHxx827+MaNF1D11n5UISh/Zx/CrTL4pMFYWIfpgfwzMA2D5qrK5IXEwIPR/sYujGSJTYCIJRmXmdxL2dm5DRiJaYZxaG7mnvokc4FP3jkRPLXg9SOjOsuXL2PC6E8hZRBa6zGoET/P/sg2cHUhaVck5ZrFAnfftv1Zq228NguJZVo0OSB3QHaZ/dbdF/RfplvhNNZfKArnXXI1H7/8DGXvvIUppR3to8CxeWMZMu8E2zOAHQwrEAjFTj5nRqMMmdxPvhRnzFM5OLmRG0eveLevh4GmP4dj9Ljp1K1bxHdvvY3MnLQ+25Zt2MGKhW9wyYh0fr8HfrjZzjKcDNqM7/BJ6bO4R4/+mjU5iv8N/EcZHze/9yjOoo28fmAU71YogBJjkHR7DkRMaEn0fC96b4OOxhpSnbDmrQ3syzpgsxLU7qA7u3xHcznvFb/BcRtnU9AymHp/OQ4h+VQJs8RII2vtx1jVIRR3kLz9WYQ12ZMihJ5cC11tYVIAJVzGmupes55Yp9VdM6+7kgkdQcIrAvQJWu3VkRh6Fn61jj2blsdyjNiS74pQMC2JXzVpPribYiQ1NZt7HarHwOrdWGpqNuBw9jIIhMAd0UgjBbPNpiG3tdUTVitRlJhLVVVRFQXN2wZAeyCN4ZNP4uRZ47pXgGhuaI3lphEEFCcZTkmk4QDBoBtpGjY7JvYuLYNAayWGJ51AcxnTfQGmeBuwEMwqyaazZg9CqFid5ai0YdUdwIj0DhCOXR9L4ukIkKWWkeUxaY8FugrRa+kgxtQwZYCI149QHLE20X19uhkGAqV5Dy4tD9zp8XZjF1Hi+/VHGulUUxlRkJhC/WnpenZKCDUdjLELYgwDhxPhdJJ5063MeW0fuZVvkXPlZRT6UugWB3dkx3LVrK3FdATZ2baYtBEt7Kp+AmvJ1l4DhUAIlZLR51G2+20sM4KUVkwG3n6X9HwGi/zpjbSVpR1e4T7oX8OjN0K67WW69qFVh23rMEza0hwEpElF01ae+kNPIGV8r7H9V3Y1sHfMZ2z4so5Un59IyGCukk9h2kGsqIBgF38e+h2kDmnucygO7+YY2YCUUda6LGSWi+IsL+saOtmnR7lpeSUt21tBgfbWBmSoGSaVsLO5ATa0oqsCX1k7bUNrcHhcqJrTjilRYoGhihI3iiO6TjgcPswLJJGEomEsIYlEoxhR2yu597MlRDQHYdMkKz0Th1QpUkcwUhtEfkkxxAJ6UWPtTYkZIgJQBZZu2kuHiug7jzjSuIp/0vMhLSvpsmZ/6J7AmIdor1iWxecbt2FJuPDsY7nMMAh1dGFETQzDwjBNooaJaUmCEYMrPrH7xnevnsywCe9/7bofxf8O/mOMD9MyKecltBTY01Uf+zY2SIvuz70fvP7eJcJhIosijNx4HEZljIUQdzvY5kBZ0W62F+9jO/vgIHgOiRW9tTT2YSg8seNOSjb1L5bTLSie2f4ggd2Jo9hvr+sgr0mHg0kuQGyiNur9xLLZBUBEE+wqPVxsqRvXTBnBi/tO5awVLxzWn6lS4ZU9vyPky4VjYWf1rVB9+D6csUlYZmozeT+/ifb2/jvGYsDywLb930jcUmMxf2V19m38fq+l4XWlkNWiM2VHhy29mKRfygQuzQHKYq8kKB3ho7owgZ5EDCMOBBhSldiL8gPgK/U04PiEZQLBMGhRPI9PPGybgYqJwrcBJ1H0Q7xNQ04fQvuMNJq319J54C1a8j5gSEytOmC90aesUGDLjtdRnSaWqcSac7clLOwxXoh4O8+bppM5eID4ASGSz/qB09PTWNfQTmnr4TwlQzehGdIcYXKVTlo6DtXV6U0bjTK2bSwLU/YTCdpxLl6tnYxoDg1bMzEV23tkZbm56ZMOoACz8SVKU/dRmXEWakSnukanJkb7dlUGCFbaddKAWe5sXKbkz6qAoP3MZzdE6fpr4meyewHl2WefJuLoex06tA6WDLITSKqnCYJPP8iKx3sauAQ008O4zzfQPHIKWXtfJrDyZfY/dcj5xxIXIgRYBopTUrKgDc1rxa+PIjXgFbo+rybw+QFSxzaRcvWlCev9z3LNpbS+drZnNeY9OlT4bdn6bZi1pThzh1KUGwsQL+y/vUkp+Ua94L3NNSxvNBn/9at+FP9L+I8xPlRFZUbeDNoj7bz9jbcH/kECvPLpe9xfdScX/mQWI4b0EwgoJZ9v8/PJV2/z6JS/MmvkZCzTZGv9QbY1lHPW0CkoQrK8bicPbvkppefmU5g7Mf7b7gmSlNAcqEUvu5bGodcxOvdYDjWIZCxZWd5KW1wrcnqvjKS9AwIFlK96gsKO9TRe/J7tNZB2JLu0TH6/cCMexeDiUfux/EsoyH8Au9vtc2ZIKckz38UbeYHv557NpNySeF02Vx3kz20f4J4TgIMlbP7sp0yZl4Urw2VrSMSOaQfKWQQ3b8K79H26Tr0WObQ4Rr/sQ1LBt+wfeDftocS4Es2RCoiYPomKUOyXFAqCFBzpWfaJxh0+9ow9or8CvEVH8Um4R3ybnk6beMAtgKhbg7btT+jp4+iYcQ/xNezuwTfWmWcsuwSvKGFw1q+Jhf7R7W2yPQTQWPcdwv4cGo7/Zc/d6k3hlpK0Nd+HrOTr8K3eYXSacHDub2OsgijS1KH7ZehUN+wlMLwUuWo2qjOAEj4RXW7D4enFahoGRqCQk89Ygqo6DwsW/eTDsTg8OtGgxulnlzIQFr0/CacnQbK0bggx4Ax6qKYxNOTmJw+f1Of72uYgb9+xBoD6rGYMZ4Tb77wj4X7e/uJtti7ZihQSv57O2Lo5FNbPocKwrdxh4fU8N/kH8HAua+f8gJFlaxi3r5wp2V0UFRdy5uxTmHxG36gqaViYXTplH66hcJvKyiw3eraflnCEcHOYoTPcGJFoTHvGjGVp7GZaScp3l9JYvovCuePJzC+MXRK7DT3a+CgAk3zHsTXwOY0LzqTANwRTSroqq3ihYCSaBeP++Guy9m6xK1QykuzzLoaYsFj8PcZICSx6iUh1E9a4a4j6M2OiK4CUpLbvQnhT6NrloG1XHvU/6+VpOsTud0uv3Y6/JqS0jiAIuS+6g7sP9XzUx4KMLz7n9IH3IQR/unQqxZleHvpkN21Bne+dNJI0z39DbNNR/I/iP8b4ADi28Fie2PIEUiZOvz4QWuptCeNouP+OVQiBy+lkaLiIlsoqyqQbb6qfuSMmMndEzww2I5ZdMz3Ly7DB6f3uS2tvZ399Ixm+YibkTOi3DEAgpxBXaz2u2WcnLLP184/JYCvDJvTtZPdUNfJxKMiYlCiRPAvTUhkz5gIUpf+msabU7rgea1jI0hmfkJdTiB6J0BFeDG0f4JoxE8tlEdoqGDp8GhnD+j+38vo8QqULKb77XLKm9Z/I7aB3L4FNexh83C04UweO1O8PrRvvIOpQSL36DUgWJFiZDdv+hHPaRWQfl7jTiy4XpKQPpXhyYmXFlo811OwSck++IGGZzfufxRyAoRRRNDCh+NSbE5ap/vJxlPBWXMalhM03sNzL7Ic6cDqZGbNQHR5Uh5vsUWOQliAc6rK1OYRASgNLGowb9QRtLTvx5Q+ioWEPHaZKIKJjmAZ2Nt7u/LkxJTHVwDIGDjhlgHgO54EASj/xva++twcnoM/OIjXHoGVTRdL96O324OU03Vy26W5Uac+oW7JDPH18ARHnAm5/dyslY1vZUPgHOv2FpAcK2DVuLBER5Z21H7N133pOmDASj9uNp3gQKUXDcaS7EU77PPOGDsadHou/6Se04lA0fRxg264PufTkWyka1ndpLbA2wG9Kf8MJI05k65bPOfG4eVxYPBmArR1Bfr9xDyO9LopeeYWv3nyHEX97grorL2fs5Yml8mvWPwNRF55vP3jYtmjFfqLPXUKmQ6POuoBo4YK4WShk90TGRnNVC02dBl83Km4gz0fgwA6Ml65AtYJE8aAffy+RersP/qpsE2VBP5qqoaoqX+w+QA6w8sBBKkOdeDQVr0vD43DgcTrwOp14NQea6kAVdtDpj04ZRUcoyt9WlVHRHOSpq2Z8zTM4in83/qOMjy69i1Rn6j9teABkDvbCAfB5E4vZpDe5+EvZHTH3fRAI8sZZjzJx1MWMyZt/SOl/zs3ZG1FfCpYRIFlIWU1bqN+g1BdX7ARg/pg8LOsrpBQJDQ8AZyyINt1Mwe3y8NQHj/JYSw+3XtOcBOme0Se7zvGIvCRFYvTXJPLqiRBtLyO46TEyynbTVViCNhA7oZu9M1BSNST9anR/TSiWiSWSBy1GLHAMEDehqPb2mfN/RGfz5ezd+RZIlUnzrsGX2pMJ2IhGWPzBNDR/BKHI/tX2A0DdwHXXPFBdO0C7FcrA1zLB5siudgLDvdx5zWR+//GSAQMZ96+qAhf8ZuzvKd0YIJJRxbTTH2ZoyXexnl+DlCpOXwajP9nEvXtA7diN85k7aG+op2mLHUy6v7kJ/6c+ZhojiIhKmkauxZmXjtxrAWloSZ73fs/tEA2P3vC6bK9RINwGwMLSryjd3UKH8POK0JAKTE/1kTOoiLnfvpL6vz2BTMZSsixC5S34RvZvoIcqSslhH5X+s0k56RiGzJiccFfv/3Eh1S1fv30nm9CF6ivx/X0OAJ0yjwxRBquuRqeAlVzK+mWr+5TPwbZbf7uoFoOGr12Xzw9UAEeNj//r+I8yPrI8WbSEW2iPtJPmOjxgTkqJJa0+SboOhYj1AUqSgSPTlUGYJjrHuShPexlnykIyo1C9YxEv/fUyZiyYQaSgBIB2Iwm1U3YPvskhj8CYmjkkA6Xy8HJh3cAjotx+4bF8+un7WFbyJrHN3wTt8NnVK9BUjbLOMgr0HG4Y+m0y/FnkZOXRLmMz1SR9WLzOSQbXYMgOvvhnAuCCL55EWlMLQZ8bkghdxSFi5z3AgEl3/MMAGKjOijSQSdoZQERKnAOdezdTQjjILhhBdsHP+i0W1btwpYcRgYmkp09DSsVevhKO2EtFCJUv3nmHYNFE5p1+OprDQSwfgG0AxvIDLPrTwxgpA6yu9w7WTQB9iJdIZU8sx/aWLtobw6R0moRn2aa0OAIKp4csorSxe0cZkIujLZ/58+yg4Ysu2sHq1auJ1L2LoYCjWyh401ou+P5jXHA+mGaYtpZGvE4NGdVpWrkBsdWPuV/DY7rRzTCK9jW7yiTtO82fxtwdFur21xibKlmcl8vHroxe5QWv1LXwal0LkxTJH4HIwVJCwQ483tTD9oeiIC2BCNYkrVLaBXeROqJ/L2M3ei8xfh106+T0h5aPn6MIqBh1P0O+9V1CDbUYjRWIxXfw/fZn2XzGw7hSCuMiZKZpErQEU3w+IrpJ2DAJGxaRqEnEkPF3S9opAUxpIoGK9nK2NW3n1NFHIz/+f8B/lPExPW86btXNca8exyD/IIamDaUkrQQFhdKWUrY0bkFTNU4efDKTcibh1bwo2Dk1FGEzQ/YG7DXxXRX7aNVbEEKgiJgwjrAj0LuiXRhaI87sYrbsb2HMGPtxDjSW4JAO1m1dR3qKHwVJVShMMGpnv1RiXa2qxLpcaVPLpF5JNNoWHyC6Bw2brZO8owhtr0JNdTCi8m1yaOXRV5YwsiibM06waaiNzS3x9OiWFYzn30iEmlhAn6baVliIMPlKDhefcmW8jBV3tw/s+RBJBijTDNg0Yql/rTVlqQdIa2qhMz2FlB9WHdFv4p4PK4kxCCAlphU5sn0mO5xlIgfwfDS0tWMMoMshiaU6H+DaWLF8LRlpxzH1+NsSlnv/0WVUywJ+MnpBwjJvt/tx0UZbVa3tQVGUGMtDxOXWHdEgOj4qaxttoz7WJizLjh2SSDpCEdxS0lbRwbKDLdS8fCB+DFeKg4qGTtoiUYQlKdu0qedZU+xnrft5c5Z0QS0YW9JQAfX4WkrLt6E4vLgz/Jx81gIe//JvvP5DF/+Yfh+q4sNVVEJ7cwPdjCWn5sNEIJwechacinKGAGHx5VsPsG3hbm4x5qE6tCP2mnaXk/0Ys7OGzCLnfQuo4TRg+caHCLj8vDrhmzQFMpBuFW+eh7bBPnY4JREHlDz9IqUvvEhXuhNLVTAdCsIwsS48nZO//yDOgkzCwcN1fKpfeoicvb+3Q52OMJbjn/ELG1GT9gQ09aLyRwAoPPtbAHhyCyC3gDd35/DtrRsYM2QkRflT/4mjwtPbnuZPm/7EpJxJkBrBL8t4ZMFTA//wKP7XIeRASkD/ZnR0dJCWlkZ7ezupqf1Y+f8iGoONrK5dzd7WvZS1l1HeUQ5AcUoxs/JncbDzIG/seSP5Tv5JDOssYXLTVBYWL8St6dxdGEJL8qRLKQY0BqQUpO3sYnpziLCwmQoytjgghSD1kCRhJeF/AODTgkgp0C0H6c527pvzILeu+A1h041PC6L0SgamxN6FkOgBQUa4nVM7PkAqMNw9gZkpJ+NVegIQo5ZNHY5YINSeE5RIwnoTnzcvxhXsIpifgeFwoDg0u8bS/p2QEiElUtfxBoM8nnsiwg2HagnEE+cR2xa7Vt+ILmeHOZIXtQcIqbFrISVOQ40zBCS96yWwrEJSHDZ7wRR9k3j1hiob2T3cR02GLxbQJxASgk5XbMlKRdM6UEyBPyoQusXggwrZbUr3XQEkqmxktf90Lpr+8+7q96W/AlHTwtEcIm9bPVGh0uF1kzbBh0+1cGCHBJ8jnmCicy0p4RmAhYWOJXUkOpaIIoWOFFEsoWNpQco+GcRp1z9F8cj+tRB+fdlFtA49lt/f/5OE1+DOq64nIzLw+sxe33AW5Z6WcPvckIM5kUPURP0KL81PocNnG2Yj6w9ycummAY8F0GSpbBj0CQHX4Xo2syrOZlpN/6kOEuH09AcZ7l4LdMeTdgdF2+3HkgILBUt2s05AoqLjJBC26Iy6eDX9TKJeT4/REit60odrGVRjU0TvOv4ytmaPQJd9vbFGkRdjQgYjdl7BPOdc5jU6CDRUI6ImimEycsXhtCz9R1lMumFFXASw9VezyLB2U5P6DfK+9zdUZ/LlowfueZZlxWNIyexAJc7kRRUi9r9AsxTGtCmc1ha0ZXhVwb6Nq0ErYMwJJ6FoKkITKJqK4lRJW389GZG1BMwsIrPvJW30OIQ/iw3rH2XS+jdovXkR2bmjcaiOIzbuuvHbdb/lpV0vATA0bSiXjbmMy8Ykz2B9FP9z+Drj93+U5wMgx5vDucPPTVpmau5U/vzVn6kOVDM8bThXj7867t5bXrmcVdV20KVX9XHPqPuwYkyQ7tfeQCkvVD/N5MAExpujSVVaec27jAMp5RxIKQcgagn2hBUKsk4gM7gcgEDO97Acafb8REpkoIb0zueJGqeS6p9oz3KlHfgnY+9g8orvIz6VVZw4eD6WZcQyldpaGDvr1uOzJB58HLROQIahML2Jc8c4EIBhBMhWG/B6LmJYej07m4dwxfQoUnYni7I9+7FgftZsDbNPFJE5ahw1jRUMi07Fa3nQhqTGGcuyPoAIm4SyXEiPI05hkYEusrpyyM4aTEtmOy1pXoZZFj7NaRtNMXVDEEgBlYEIzdnZnDbSh9ejIKVp80t6a1DEdSjshQ7dhKe3nQfAI7nnMjcnRF1jBVVGLSfqE0lzp8Vkve171W30GEGB0XUqiqsNV0EacdpML4KRRNIaXEuwXiFXKbaXVqSFFBYH9AgCyeDBRUSjy3A6I6SqI6lXy2jIyCHdM5P4yCMEgYpOqpTjmZHmQ2LHBgSCZejRdhTVi0ShvCYVpSbE5Fwnn1UDepTmcp3BIxxEscXI9ovhTGQtmBIFFw6RihAainChKE4UxUVbTZDmsAOn4aa9aiOv33Ubt736Qb9tXxGCIVnJmSxbcxcwJtrOdSeOiLGmYm3fit0HU7LwoxfRzAi/PDYlTioS2N4KWyNLULdkHyN9Q8iOmV1BFaozHdy/K4IUFkIqSJmF35jC2LkuO4OylFjdzxq2JkTjhnXUblqKcs3FLMi7mXDIYtPSABLJrHNLsKSkfovd1c29XCJiwSYypvHSbZxixfZt2Y9Zxhe1NLnG01k0BqeaFTs/M84SE1YUYUXBisbOXyLNCIoeQKr7GU8DSnoLrpRhWDE59O42VXrsCNp2Rql3NrM330lRro6kgcJUP/7csSxeUYExOg0FSbtf4Jp0CqdNvTh+D6SUfPbcr+lasxrfvlqKaiKYfouJlduof+BMUFyAIMOs4mDqRRT/+Jmk97QbB4YOZusQL0PburBivhJLCvv5F7bBFXb5WZ6vcfaOCAoqCipTsk5GFSpsaTxsnwHuIizqydHuwLf++7De/r6j7Qc8E/47/KoBYrEdFiZSSKSwn2v7c+x/IXt9ZyEVC0sM4UJuQ0iBHNLJZecdNTz+f8F/nPFxJDhn+DmcM/wcLvngEkZnjub8kefHt1008iLe2PsGj6x/BI/TzZmzDmc9LK908UI1iJCDSCc0ksFdlzzC+s71mJbJu/veRbd0/tbk5g+jjsevNNDVtZMTBs8jPb0nyVZt7VZ27nqe4kELGDfu/MOO040nKnayU0nh9vNfOGzb+PZO5r9rB3u5Oprt5RxF8vPzDpcfXlL7IrWBTn5+3rcSHuv+ro/YvytKeUori1JKeZ/7eaGmnnFj/457ns0SaVu4n67Paxj2rTG4im3rN9jYxsGF62G3m/lXXkR1sJ73l3zG7AsvYNTkKf0e68WPPqdr3VJuO+tUctKPTKHxb6v2wLa9ALzUfB4/++75vL3qBZ458DBnnfhbSor7Zw0FGlpp/f12IpMUhp+XOKtr008WUZAXIP/yvlooS372MwYPrUcoi3A6wYjOYcyCF2n94Eys3CGYuT+jY+lBtBwPwu3gC38z7Q6V96b1UCe2bX+choYPia2kcN0Om5K5xesHbJbVT2cN5dZZJfHfPLOygMvNC6k9c3IfLxOAYVjc9PBKPm3rias4W2ti6tD+VVMBe/Y+gDM06knDLCxg9HmH59voxq51KyjWw1z2jRMSlrn83Y9oCi7h3FseoOaTrQyPeMl37kXN1pDVTmRBF+YHK7D276bkN6sT7keW7Sdnbxs5Y08je5x9fxve+ozCkWHOn3smAMvKd7Hz81rGTj8Bl/fIaJjG6mtodY5i6FXPHlH53vhq7aMM+fgubrzgJoqK+79O6yv38avPzufW8VO5fkbPMte7++r5ZGUFjoouFhyTz7qDh0e9CCE4+dq74Vr7/yf//ibRnY24ogvxu3VUGQYpadfGoY4/PDV9ImQNKsYbCbD6/MQeq98v28NfowFG/u6MPt9LS4JpYeoWRtjAipiYsZelj6EluBSPbEIzWyHcRuZmHfZB5iwdKyOWnNKyl+ikRXy5rvt7KWNLutJeHZWWAqaCtByInZk46xNU+Cj+T+Ko8ZEEXs3L+rr17G7ZzehM202tKArfHP1NHv/qcdvS7wcRw44JUK2e7ccMOoZTU2237zfHfJPH1t/H8tpNeB0p5OYsoKtr52Hr9rZ34wjW86WFkqBMZqofb/tlBNNeIeyzVch+dnx6v2WPIEYwtlwhWSTX8tRjJi4zi4rTowza9GO2BP8GliT94Gn4GE/VE2uJOEIIRZASSccfk17yZKZjxYTektHzehgDyevUG5+vv58pWgtiyIW8eOW3YnW28dLzz5BipcRP1u9xM//UBYyaPKUnodxAB5Mm0pTU1tZimiZ5eXlomoYA2h1ddOfMTY2pqwmpYaHT+voeAMwWmwmUlanhcPYdBIcP+zGK4rQ9PNLAP9VLx0E7mC69wMfYQWl9DA+AkCLAhLv/vBrdlOimRcSU6JZFMGryZTDMTK+bY4szeLS0FnduEdf9JrFmBogB24Adh5O8jFAUrAGCdzO9TghKZs0ZzC3bHmZd3TTW/+hqopaOU7WXB/Z3bsLY05Z0Py01lWQB0UjvWJwuzChUbC8j1BmJh/QEO/UjNj4cRMjpXIp+TwECg4bimym67tdH9FuXatOozTAc2NxISqYboQikJVE1hYx8b6/23fc6FaW6ERK06iAPjMzl5K+grjOxoBmA8WUmgkwWMxqf4kSalh0/pjkQXwr4cnXPMmX3Ep8Q9PoKhKAmVyKKB74+/d1+W1lVxaGpOHyJ9jE4/inLVQX79nDK7JnkHJIQ7+ti89KDrH5nP83VXWQVJTGuj+L/DI4aH0nwqzm/4sfLf8z1i6/nlbNeYVBKj1SpJS2UBHQO3bIDRc9ccCbH5xyPz+frs/41KmMUV4+9mOW1m3Aojl4DXt/9WdaRGR8mJmqCfCpCCNb+4BfcsXQHHx/cx3GDqzl31tUJyiY9jF2n2Ps1H5fw5QhQXVPR2k7kuSmvg6udGaxDZgp8B8fTIZtRpIqMWpgiiqPET8l5s3HnpSLLbYpv0sy/3fU5wrCkp3/zayZts8W10gv34nfZHaDDZ197oblwWBogaYtadAUjvPre+5zd2cn4CVNih5Ks3NNIV8SgJJb5eHCmhxR3rDOVFqGuIH9/8kkA5s2bx4knnogiobp6LJGIjyElm4kG7OA/gQNJlJR5g+hc0RP8astg9D0vr7eE8eMejv/f1LgZcmHTiVMSnnNZTJZ7RX0HLiFwKgKnEDgVBaciOD3dz13XTCM9w8Oj99RSPH7SgNfRGkCZtL+6HwpFKAMqnBZleNFbY8kXU7KIqH9j0t/t8y90Kvgk3FAXYohU2LtjFwVDhxAMhtnx2QryRgxj3DSbMpozeCgW4EntiZlQFIP68nQWPm7HRWjuEOAh0BYhI+/IMlq3Tf4F0drd6J4SiioeoajyUcx7nsDARVP+JRR95w8Jf9sdnVS9uZ1Nn207bPv4E4pIOcFuU4cyo771vL0uMXp4RtwwaQ0lTyr3629m4gtZ3LysE1p750AxcDj7ecbkIQZETABPT3czQJgZZlsE/rmk4H2ganafZUT+9WSOo2bl88Wb+9i6rIoTr0jO6DmK/xs4anwkQXFqMc8seIZLF17KT1f8lL8veBZN87Cschkdegepzv4Darp020WelpJGQUFP2u6V+/9Brn8wY/KOxzBs+WbLisRH2W5PRzeO1PiwpDVgWicFk0x3mJeuvTFhmYFJjWAhUHvN1MzIDsqGn8preTczV65gButoj7gYBIy6/XR86en97yemaqgm0d/oPm9zgEEMbKOhfdva+P8dHT3p5DuD9rLDeZdcypThUwDYd+9yHCHbfGz+zvcoN6OoueMRI67kqmfX9d41C8bn8eSVM2LHMXH0uh/5+fmAbTaONAXjC6exX9+NJ7uGxUuuR/VvxhmaQuppxbhGZoCUKG4H+9/cOWAnf0TwOCAoWXzvqbi1JInzYnlUGIDeq1oGnVtWcfcN22OxNd3hud1hzILhlgtn0SySScMLRemX6dG3UI+rbW30DdBAlWAKqNHt324ODKXEOIhx4QVsysrGEwqRH7ufu4Cq/CIG1dleJqPXMzBubjoHdzZhmYJAu4IZtb1uerBvAHYypJ/fQ1tuWDQMZff7BL3jSKl+D635cIPikAsAQPYIL3zWc6O7T9nj1+LG9Qs7XqS2s4l7T7oKgLljc1n+RSURS+LVbBn/kTnHDljfgEfhkTPTuPrLaoorPRS76zgYzmeot57THkwsUNYbe5eUstE4XO6+N4zmECT0bBw5ur2N8uu4NhOgqtR+3ksm/mselKP49+Go8TEA0lxpPHD8A4x8Yj7aBnugGaOqLBIgqab2vlyksAdkTUpUKWlUZ3LzwT+xbX0nmzyv2cyHYDb/mPoUHe5mjm84iSE1cznL+R1Ks35JlyeMEPDiS09hRD0MG/4lKSmdmFJykBLu3htBP/A5QkpU7MHATotnv5otOz39OS+c0ycZnhKj4ioo1If344pYbPv2nB5jRsTIvTEGSMAxkUDayZz/u95JUPp2DI2tBqeEvTg8JyKtMF3eNLYMruPYHVsZX7eNzW0z8Ogp5HmraXikGs3t7svdi32uCFWBAm+++QbpXtsFHU/MFqNTlje3AfDttzaDyx2jWhIrQ/z/odsD5EcgnHclnqa3cJhB2rqDCqWkpa2OM1J1dm35LXX78/mgHOb4T+ad9CZEeBnKTYU8UP0d3oz8lfmrtzIsbyYHelFum3e3suO39mw0YLWxo3IFQX8lwZEKry7egrJUxXTk0+wQVHQGyTML0LQIUm5CiFQaW1IQmop7RHrPVT0CN1Ox20lrNPlg2d1vJ8sybB/QYlpEJby2i2c2v9Gt8h67RiI+E9akimYFCGeMitFmFbpJmhIBlsVrC74BwO4PN/d7KAG0TT2WsBnkb28v6u/2AxAuGUKBxwFS8m5VDevcbu7PzkRIKNKdXNpVj5bh51ff8tDl8ZEaCBB1uKkcNoGsmjo8EZ3UYABnNJUuXx53uD3xfEjzLu+RbH/+Z+/Q1WYP9ouf2k6qS43HDsjuExdgCMFTx/vp9CooEvuFnRZJYRzq0PEoElIzJ5FCM8qHr+FA4ogF0DoEaELQ2Oggs7qLc7ZPh5ZHKPGlohxIBQOEwwRh0bS4g+iSKJcGTN45ZjfLa7Zy+7svMsYzjqKQxQUjdCyfi7c2f8jpqTpVu//CA2WvoWBT8tUYtV+JPeeulOuJqPbAmzblLaZ75zL7R9ex6u6X2dpQQOGznzDh2sT06Z52woAZst3D04maAT7aXIWmKGiqglMVOFUVp8NOde9UBZkpbjJSErNr4sbHv2h7NFR08NmLpeQNTaVkYvbAPziK/xM4anwcAabkTqFp1vX41tpKngWmycrBk/C40wGQpsGsA1/Gy0/rzGULoPkkjkKJ2WBAEKZVHItXT6W4y5Y494ey8XfNwXAECUdCZKTnAm34/Y1AEYbDQYlRzlC1jaCaG6P2gdkdhR57pRj5dDrq8CpeDEvHNOtQ1CimVQBCQSLJblWZXqqjdImYMJUEaUCM9QEwrauCnUMO0uo7JBNeDALItxTGR10oviFYZiae1t9zzidgePy4nE50HfxSITuziE69FRntNeDInj15TBX8EIhEiYRbetKedBeyKQiohk5NfQthZ0o8WS+9cuAgJae12LOwZkcmrw66EmSEcLObF37+LiBJ86RxxuDjyC5egWm4eWvkS3zS/AyewHIAwt5jKGz+HrsHH0dKnc790keZYsarO8RSUDoiCAkbmpcSMtrIC7tpDeusn3oQC0lBmkK26SJY3UqrHMnumlFxdoNMi3JoKi8pkmucgE1xHNATFduHMsCAIRTB9IgDl/AjrU562Zw2rbqbCSqcZA+ZylW//UXCfT2+bDMAmYd65HrV1+VNJaBbsZOwv5WHBBXVZ+TRkFmElJLhUYPh0S4u6bS9ht3+mVdSDrI9O4v0tFG0SMP2DsowTSUpsdgYP9FoJ4ZRBrINODxJ49g5RWxZsp9IxEW2x0N6diZCVRCq6In1kZJWaVGW7WBWJ+Q5HJiAKcGUEjOmqGIq4CATr2ohHComEl3a5QwpiVqCzWVeppVLhm6vpa3CgaHRw+ZSbCNONEF6i85oA/SJKcwZ0Q4coF1vY4JfhTRQNQW10+T0NIOl4XrWt7US43ZhibjgPRbwYOejHBRDUArqmebZgCerBbiOufdcytbvrmDFOo0J1yZvIwBuCbqavDHleZ2Eg0GubW1KWs5pSrYfO45UX/8GiAx2Me2r31P9HZ06txMU1Rbei2XcRsQyBAvR9//YZyUahs42thedj5k6hFOuGddzP4/i/zyOGh9HiOwzHoZT74fdH8Ib13BC5VY6rJF0OSKIQ+IWhjt2swW49LLB5E2ZTuWu3bz/p2rGtPToDGQUt9N6MI0pE+9mxPieIKzOzhrWrV+I33cBWSUn0bT9fH4weSyzChO7Xf/06BBycy3S09pRHQdQVXvWXlh4F4UF03G50th08/fRDhxg/MqVCfcT/vFP+OXKF5j+tw0Jyyx9ey27FweouX4G14zM493rHSANZo/o9l44MdrTARh5+6k4MvrP/qosXM6eFz/kugefIn1o/1l9//7++zS+/BTP3v1tZo5PnNvmDzd/ylq3wQaXQY7i4MoFWexpqwMEn+5sJxjI4NXdF/CtE29hUsl0WLaZqGtU3PgIpZzBztw9rPNvZ9aoM5l92vHMTnCsD7/ZkzvDWZzDR99bnLBeANc/ewVaAm2FgbrJI1kG6zbW1AE6XUUoOKQgbWoB19yQOHfNH694H6fbnXA7wPC2BnIxee78M5KWGwhnfrKV7VYUoSjsO+8DOpY+RHt7OyeqWwCIovGedQKKtYtV5yWmir698gXuKXs4YWd2zDdmUTI0g5fu+xGzvnU3Q0+c1W+5HZWtsK+C20bkc8K4/K91Lk1BnZs/3E7pvmZEQKfAbXvehr/3GbmF/evGbPv8Dbj+bualV1Mn/Zwzdykpnr5lo+0HWLnxVH405ipypyYJFL7Xjnep73CyfWwqrd4dAKy89w0gl3E5h1Ng+4MuJY4BVsu+dUwJp3eECUdNdNNCj1pETRPdkERNC920WF7dyuNqGN1IvDNfqJ709v2ERs1GenxgmgjLBNOAGG3bpjVbYERtHSDLBCnx1OyMG+8zLvIx4oYTcLqPDmf/P+Ho3fo6cDgxR54Rn5VJOZiI0YEjw0OFVURXSwdbIqMZLu31xzYrhTxg8NjRjBqxjT37MgGLEXkHaWv3AGkoh6gOdna2AeB2Zx9xbskJE5YBEAyOxOU6i5KS8ygrv5aamh9TE1NcNtpKKGhtw7IsW42yH7Q0HiTHobPok+/Ykw0hEEJl9Ogbyc0dhcPhwIjatXqnoplFpQ1c4TkJM7yW/XtrkEBb2EGhx8fIfBAkXjLojmdJFnBatfANGieejvFqHR8fLzjjtL6yyZYlufmdLSxOtxkkHsXi5mlhUtoCnDd9Gh0iyMn56+mMunnoowDLFr7GMvNdHhjq5Ocp59DoPx7NilBU+xFZl/0dPjgnXq9kUNxerHCQs795y4BlJfQb22GJ/r/vDd2wCBsWD2woRxECNX5PbKNDADs7w+DoYQYlrLOIPewDisSKAa0iwT+T97T/Q3VjxJQTYMoJvLJ8CxMXl9Fp2d4szbsKF3uOaHdWglqFggHKyvZgaa6kbKZFzbb2emcy5b9DEImajL5rUfz/wqFp+ItSmbNHwRAK3sz0hL9Ni3QSAPTUMZwz97nDDA8AM9wMgKodGdW802d36YVOO8lkY50OKqTnDZCFOIYoEscRxGBkpiY3UJs3beLTX/+ERkWjyelBaB6E5rb70OaDOLKK4qq7o+++Dd+MryeJXnHlVUT276fktVdxDh488A+O4v8cjhofXxNdoQgt1mCeME9nn3kKFzoqqAy0cvvttwMwHti+dg88V8W2N9ZTtXAVQoHKmky8ahvp3k6CQRXL1Im4GvE5MoAh8f3rehsAXm82XXHJrcQIG2FbdVEKpkx+AD0aZtiwYykrm09E34GqtuFwRMlOqUSLqoS+KsU3fVy/+3JrzaguHViLZUksK4rTHWLP3o/YvUcgpeCrzmtJ5Ri+syimIumagMM1gcnnHGT6Wdew5em78DYY0AEiiTT4prpKAJ77+H2cmem2SzUW8yENg+Z9u9kx5xoeLrUpixmrWljhKkMogomT88lIddMWirJ4fXV8nyFL4Z4Ndqe4oO5xLhn1Hl6g6eAEvuGaSmuT3QG3t+vcwlsIYS/fmJbKY88/jpqhYljJYywUNQXF68YKB/G4Bw75l8iErKiBhriapiAyzcmfYgZpv3CCog88WERNiSrB4UwecDpQdlI4Mo/MP4vL5k/mxAnFPPrhRtZXdlIulQGPZkj7nmlKT3vb9Pkqtmy0PXgVrbG2OmIibeHEwZRT3LaHyvU1BMZD0R5j9dlbZnNSsR138dkvv0RXNTzOxF2spttMpblTftWv4QFgxvoDxZk+YF1M6WH4VVWM6BVUfOGTV/DELcv5cruPkVWN+AclVu8FiEgG9HwcCbRQE4qUpH7jCtCjWKEQVjiIXrYHxZ+FkpKBbLeFxYTr67cm54jhhPfsQRpHHkB8FP+3cNT4+BqwLIvXX3+dauUivApM0tawFyAM9957L+effz6TJ08mpWM1EZcHM9BBe9SLJQUp7i6mzc9k+Ll2mvWyL97hhSVbcDjH9jmGadqzeFX1xNkCIoGeSGPrBj5bfyn7981CbxjNF5+/B8AvfjGFk0/ucVNv+PAKUGwGhyMzrd99AXicVaAITl+wiarbbRXXgGjhi4yXcclUCnxtpJb1Tbbd6KtkQeqfcOwYBmddw+Trf03w3bdpWQM4Eg90e2orSAWMz95HFwpKL2aERKDnFjLJqqA7f7k/Cv6PbarqusYgCy4YR6bPyfwZhSzfYLt3dt55PIqicOcTL3PGqPfi+0tLszu5b11+CqNGHi74tGLLCpa8t4TjI8cTSAkSCURxJYrmFyI+Y/O6jsD4SODeSOQR6Y0iRaW6Q2fVvAmxuAMwLdkTJIntmS7wOQesR0g30BA4+6Nd9q6XNFEdybsFwb8eJNizp8ORn53B/VefAsB33q/k85bkB9OlPYi71J7lrfeXfgqAahq2p1K1Yzg8aYnZEOOzU6C2jkBAT1jmUKR7naAKjptVFDc8AKKGgSWUpMthwTZbu0PzJ66T2bAtdh6JLQJp2ZoenRxH+iFsJkVROOlEjc+WRVnzxDJOue+SpOejWxbaf8O9NaMRLCEovO+2hF652gcfZOuHLzCon5gQwzKwLBOno/8lS9ew4Vjt7QS++BLX0KED1kdaFlZnJ2pa4v7vKP69OGp8HCFM0+SiZ/+BIp1MTFDmnXfe4ZNPl9KuOdAyytBHp+LNcJFbuZdzGrfADkFg5xN0GJKt7kKgiLtXbCG4rxOXqZNTuZ/xxpfkjIbKHT/F7coBFfZ8/jd010d2oFp3fByCdvaR7ZNUBrPJHbQ9VgvB1m034VC1buUgHIM8hLMFeonFp++/i6KoKIqCoiooauyzIkgv9aC2Rah47g66OupJS70ah95Fzo5mFC2VkimD+Nvgdxh78GwqC9ayJmc5CHgLeLlxN3Xv/xocTtjjB3JYv3IlwmEn5BOxxHzdr0GTT+OuE77BQ5F2UmIDouxN61RUQgcE7LWoP1FibDcparSb6768Wvbs2I/H4eGc8LNUcSKFjhBtm+2O5cczx6KHH8VSOqjvfDjuQdq9ezNNjbXY/NFuuTSJExg3IZc9Wx2sbvZS+Yc1TDu5GCmj+EPlDLd6BiPLAhkKIoCFX32Kr3RTLPGgiCcgNA0D4TTQnCrbxG5mhidR/vmu7tuDQFDUpHMgXbBm15cx0XU7n42tPm7XLeR04zIE7Tu/QKUn+NEwewVCWlAXkwU3LNs4MUwTyzQwDDtDqGmatAVAo4DGZXVsatuE2WWia2NAccUCeWNBoWYnFVsW8cgDRs93sWjgboMjMnQoB1LSuWnhYrvuMbEqQezSAq4OyOnw4fL6+4pbxQNbIbepi+IUwR1Pro8zTgSCQRWbGWQ1IRwqQ5o/ZKavjS/eusIORBQqUihIxc7KKxUFq34f320aRsObm2l37e7zTM4bbyustnW0salmJ1tXf8XBveUgwKFpODRH/P6ZEsjK4LHaJqq6ojgARyyI1ui5RLasu4gFe0qJ5VZZtbqKu9tM0pwO/C6NzvIWThhgKay9bh0eoGHlKygul81Ciz0r9oVSCFQsp84oZG1zHa76xd3x1rFgZtsQNcNBqpSpeOtKSf3wUVTFgVDshJiq4kBkK3SJfXzMUA688AUlM4bHlvHsl9127fwtK5wGXQ6FVS0dca0YlxC4VQWvouBVVTyKwKGIpEt9VjBEOMZQS4QVpR9x3/UOcj+6iO8Uf4sFJ91Aij8TKSUrjptIYQs0ZzhQf3wjx178/fjvInv30vC73wGQfv55Sa+xlJKuZctp+N3v0MvL8Z1wPEWPPIKacmTLWEfxP4f/uMRy/wwCpsnv9tfyZHUTqaEuQi4P8zau4dLlH+HWI6hRg5DbzYZjZtLh8qBrLhQFvhw7kYPeXAB2LP4GKVYIsHNgbHeP5gP1NN6dfByNKRmYqkpaewu3rbuPYaeUA+DULVRTMmZrGGn1dQZ3Z0Hp8sLqQSVkZNRimvbgrGn9z9yc+wS+P/sRlkSREiGt2Lv9/5Hg5fOH8t6YSpyWRlQY8Zn9ja2d3NLWjopFs/5TQta8pPvZaJVz0xmJzDgb/7UzzCWVPZk6W9R2rhj5iz7ehPO3/Yi8rpKE+yg45mncedvYsOEbWNbAtvai8cdQnt2jzaJYkjveaI3/r3e+gWVUEtZMXju5CnkEiXbPaj2e79UdnnPiowIHd0/qPyC3G6Ilgmt9clZBwt9i4cBCxcQtJTe0ZwDgUroQ0kLiRgpnvF0JBG3NdgbSgJZC3/iPnta3ecJUdo2aguJw9Ep/I2IUTbtlnrLZZHSNJOxWDls1ETFjRotK2p2CV5092VDnVH3FbRtfokvzIJC4zTCaajHkonqbWi57aOaHojL0PBbpAGx0lLFVO4gau0FmjHqtSgWnsNuBKS1MLCysOL30rWnzaEzJOOJrDKC0RNC2tuCIWLEcKPDN3Z9ywf5VHLN1fcLflf3iJsJvJw4A740rFtxFsyf5rN0z6HkcKaVJy3RmXE045ZQjOmbC43QsxNf2OmAbgwgHxDJtC+z3Zx+swqtLqoq9SIeK5VD4cOZp1JZMxiNUnEhCzUvZlr6SMS0eSjPtNjCtwYfD4STUbqeC2DrUvn+3czrzZlxMeu5gVl14Ei0pggsefA3PxMR9iDQMan7xCzre/wDvzJmknHoq9fffj1ZUxKDHHsU9rv/l56P453E0sdx/I+ojUSZ/aUeO3zwom+lpJdywvYxRFQcYfuAArQ//Hvfv7sftgLt/9WtOfHsRbgEfn386XZEII77cxQWV+6m6fBELGnvkn8/avZVnbr6KF1ZsYZjbyeiGStYoGjfc/ylrH/kuGzft55Z7fwIvXwSn/w5m39Rv/dIti6Gvj8YZzGTyuWv7LQPw3OpbUEdXctUWO6GYJaVNDZQSw5JELckHd/2I2e9/StgJtcePxjd5SmymqpAzeiIjps/nu3/6hJu2pFH461MwdYOdX21j44YNHAzW83dXARfdchm/fesu0iqWkje9kdlDTydv0DG2G1VaWNLENC1c7y/hgx//kdSXnyUtq+CQ2Zxdv1U7/0zj0uU4n3uI9MwiLMXkIeNpbvvsOvxaKr858UnWRzbBJrjwpkxcLgfQTZ8UoAgkv6C8di85TYJ5V7soHj0+nplU2Pl6QULEtJi2oZYLMzu40dvFL+psieZcpYlrH5kdl6H+bMmduJjPjHm3810RG8BME9OyME0LUxq8/vsvcKRHOf3qaZiGQY6R2Svuwx6JW1+9mclS8Pmoh+3EhCLm85HYcS9gy6V3udHGpuF2KDhUxZ6tKvbLoQqbxaIIVFXgUGLbNQ3V4UJxukFx9Ctda91biD7sZtxX3d3n+1G3B/nxhCJ+csWUhG3pV1dfxfRAlDt+9fOEZZ5f9SYRFX7w+4sSlnn9gfW4qrrY9Qc7/4reFWLxt58g4NGYsWkjQgia776Wpne+xH1PW98fSxlL8GHS9dLf8ZffRt71E3COtJfphnAiF/Qq3niglj///UkuOfV8Rh93+IAlpSTYGUb+/rdMnzif+efMJRp7LhTsmb4KtmdHgIKdRVlFQVVB+YYtrGYZFoGwwY6fbcR9YABxwC32MqLjZz9AdbsQ0sIyTCzDQFoGVtSg4atSvGvW8uezCxg8qhih2Bo+8XehUN3ZzvnPVXDRkPP53tTpmKaJZRmYpoFpGUjTxDANLtp4C7M8Gj8ZNgRD2oaSYUosabdjS0LAtGj2gFQV9FgfoVsSXdqy/RFLsrStDlPLZf7QS4haBlHLwLCisXcDQxosOn83F7z2FfqQPIgaEDVYPHkePksyKBBEVwQ1BXnIkIPXf7iWTWvf47XNL9DhCRAygqR6Mvgivz1+rR5kEQ9uiAX2XmcPWxm+Ska2uqlo2sewrU2ktek4cnNRMzKRkTBNT/yVcGkphQ8/TNrZdn4b76yZVN5yC3W/uY8hL7/0tbPoHsV/H44aHwOgMtzjRfhrVROOyjqW3XJl/Dvx4IOEgl34WlrZ9utfYo6bhSPWoEMNNr1tdLCTP27aCYOHx3+3ZKidK0YCKgIViRkL9It5oEGPJQRz9j877nrzz9T85jG67rZQW5oHOJP4XgGbNeEUAifERRXWz8ihpknlgi9Nhn66Gz7t7cJ+hU+vnM/QlrF4ZAqqT0P1aUw5aRZTTprFuo+/4KO1S/jizWVkKIKwgD+1ruKJ5pXc23IB58z7VZ/aVPvT8IeC5GSlk5mX22+Nh2Xl4Ag282Tl8zRUtPOzmT/jjV1PAfC3055kQvYEWgZX07AJXMOGkZHWv6XdYRlYegsedzp+f3G/ZZrDQaKOJt7uSOecfI3C+npqZA7zvY14fD0uWtVhoKkO0tITW/U+MwWvEIwdNDZhGd3VjNdQGVQ0MmGZ/1kYoPSNazENCx3wJgmSBHBGOvFkDizmNFC/3ljRadckFGbTJbfg3bee4dLgYK468KAgBKgOwIGSbsfeKJ7E9e6Wek+kAyGEINAVQgDpfi+pzn9OwVNxqqQ5VTwOJa5ymgidWRm49sP7Hy9MfrHGFnNGdh5FQ4b3u7mjSQMqSE/NIW/Q6IS7kZs0snwejhny9Tw7h2Le7jAhZxaPHptYLZlTgF9C9xOgGzrtKzZzelYXf5piZxU//8MP2BcyeHr9z3E4nEycNS22HKSgCoXxoTZMRzYYUF2/l72Nu9iv9Xghf7bKVqCducfip29ZNKgqmD0BwK4xYyh+9hl8s3qo1e4xY8j57nepveNOgqtX45sz51+6Fkfxz+Oo8TEAJjs0ctsMGtJjFLZILZYQ8WWK9KYG9mXlkBlshJdfZcKFgpqZdmMvbbWpew+MngJAalcnV3U28njBMNxe26AwJURDLawJGahKCKOxsSeYLxpzRzsOp8kZjfVU3vk4ILDSwUofYNlEWgzEs2zIcvP5yZn87Mml6JEglmkipcmGN54g/5FXGfLichxjUjGHlhz225mnz6G9tpkvDm4CMhDAS9WCK4rgF+XvUJI9jvTUnoG/s6PKTsKWpNM1VcHl/6UiG20Bt6sW2fLTJaklTMi2dT9csfwtgVAwofERl69PwppwYwf66qhcvscCbFbAJ8EiotEouq7j8/mQsZiKpDiSFSwpj0jl9H8KAgMUJ3+++TMAfC5Bs9euj5XkBCxLokgTvzc51TKuGpcELkcUf10pG775Gml7V6Ofeili5Fhmn9NLtj3UMmB0q+q324BIEuAc0e1JRDQJO6K91RY4c7kTq3IeMSxzQOtLHTEc1m3kwhtvRcZiahRVRagqqsOBUFXWb9nJ/s/eRXoTU2WjMXq4YwDpfKQ5cJkjQM6WHYwrT+WeJWfhLMjkjntfHPA3rdEQKE7Se92jgy02G+mxXQtjUU4DIIE96I91k8M3rUe0dWIFurC6unCPHdsv4y64cRMoCmqC1A9H8e/BUeMjCSLVXSy5bxXXChcRTeCMSjqKNnDWNx5i2Y8mka34qDp+LiOaG2lIyyO3vZ6O1Ewq3PYg6B9SDM37KNRDPOhTOC3Wqf5txRaKXE4eKqslKiX78UKOl2M2reCFG19nzCyH3W/FsuOiHd7RhzZvAsCRoqK2gNMaaDYz8GAXNUMoiguH5sSh9TAoTrzhHiJX/ITGqr189eEaBrccvh8hBKdeey5bf72TTjNMFm1M1is4NZDNEp+Xb224r0/5YyosfgJoZuLBQPH5kEHBSTlzmT5kDk2hJjRV47IxPfETLqcGRAlFwgn30y0nnyy8yeXw8JS8EiXlBAqLb8IUDgypUugbzH332XUfPXo0GX5B48GOhPuxjzOw7oY4IgvlfwiWhcBEKhoBIalwmHylmdTEGEeZSSSxkRYqFmIARoyEAbnEI1o+J2/7m1gomN/8LpN/+b3DC9VuJeGo0/doSW2dtg7bhd/Unjh+pvaArc9jhf8bjEJLIgfwfAjLNodLTkmcvn5Lm200KUlYM1Gz2/hIXEZKaccAJWDOfR2UBEbjkE2oEYl7VyvBSBdeV/JMsm1R+/lMUXuO/8Nx5+DqWMpF85ZjWhGipo7EwrRMolaU+W/aInZnF0zgsik/R7d0dFNHt3SiZtR+t6I073uBiFaK0+WBPA/QvycVoO2dd2l/+22ybr7paMzH/zKOGh/9wNBNNj2/k/WbGtF0nem7n8UbrMcTauIXc26AXHhnRRPZZht1x18HXQ0MqiqlK1Xhy4nTCLq8fLp1GfWmCqSS4UtlucfL55vKcCAwDIus6q08EhgVP6avfSXf2LwVT3oqZmUnea7hBFd/hWqNQV/zDsEaHUEvqeGYiqnRadIVFOAJsPbAS3T3wN0Dbfds3x/cSKuRz5KvalGE3ZlpLfX4XBFUVUUoAvfuTThdtazdvxZFKKiqGmdwqIqKmuJFVVIwRQbVjV1oAlQUtFi0vCYEw0um0binlBOjJxDU3ua+Op0bHQbN834cX6dGKLi2LAL2oXSGiaQGIZbbxc5FYyMs7Y73xlFXM3rYzPi1EgjMuEiZCkTRI1HMaEwVsfsaxP5Yhv1/NNJJKNgAQsE0AEtBc2l27Ie08BEkz+thbPbofo2H3bt3M3uGSUa+j3DYsGMuVOWwmEzLsgZMBlgY3Jl0e1LEYmOg/3fLMjGjEYxIiGg4RDQSJKpHkO0tpOshhBnGDeiVHbyUGqGjVwDvU8dlc+JJJQkPHY0ZeeHKvQPUceDT8LlNIr5sRi/5CE+mvbQVrNtLqGk/3cGuXUPGE63bTdfBT2JtB8BOGSBawmimG1ljK6JG9lRCgw7dTAylJ1+QryuKquqk+BRCoY54W1NVF6rqQAhBWo7tjXS7LWRXM2guDOkkqtt9gupQQJW0Rlvwuj24HM449UWaYBgWpmHa8VS6jiaEnTQtxk0+TD9FJvPF9ZSB5MasEVtSSubVMGNJK/UjiZAeAG5HHnJQPieeN58vHnqMR358Bd/8r18xakjijMnB2ETKrfYYkpYZxsSFomgoioZ2yGg0L3sQK5qqWFi7nQdOS7zvhbxDxDXweTU//TQNDz+C77jjyPleP4buUfxbcdT4OARr3t3PxkUVABRqAl9JITuVa8iLHMBq3k+Odwxg8eimmHRo1lj7NWQeTiCvsYay4hFc3tzjidgRjrBD13vcsIrg0j3/YH52Pr8ZdjMAvzwwk/lFU+O/GQa0VANcREH5laRUvHlYXbMvFJhRwaLMHCZ5dbrK70l4XpkKOOqHsefdXX2+n7nhQdxdtuDXvcDmoYLrXdcn3M8lrqf583wXbN/X73ZRlIOjMIc32k2+sfj5ng2v9C03budaPMDBcy9MeKxP5ytwrMKlX9wIX/RfJrdzCBfwY5b/vpLlVCbcF8D+sl9R3X4waZn6+neor3+nz3czZqbQ1FiMyx1A87axqyLI3h8mZinM9vopaFPiWikybgL2/P0Lr/EOOtz+bg+9OPb77v+j2GwSLxEUpO1xwPY8KEgUYZEpQkzV6nCLKCYqpr0lYd1u4B8UUQ9AtNXbx/AAuPHzJu6v/4RvXXdO0usk+vHG9YaUA8d8CNNAOpxxwwNg3eqzMNN6LWudbL/q9x2uJquYknlfNqPETqH1486E2qtBVx1z5r1GK6/x5eq+2ywrThRm9rEOvlxYwpevtBy+k6+Bk76w21Dp+AksHj8EQ1VQLIseVpDdDnyjB5NM27NbbDTZpezxfCS+74ZlEDx4LQv3pfPRx4uIc6Njirnd72m65GKpcbLmwlIEloL9Lno+L4jOYJ+7jjnTTyf8ozBf/f5pFn/8EqNu/l3fulsmD6z4NpVWNqu1CwA/LqVnyHFFD5IjK6huXIkTA0WxU/jpwRQUvJyZex4rmh7v93xM06C5vQGn5iLa2YE+gLR6cONGGh5+hIzLLyf3tp8M6Lk7iv95HL0DhyAasR/kE68aQ61iEdZNhszNRVUmogjBAyNT+Q0g0aj+rAL3Vw2kXD0esW0T4U1uMqenoufnIAQc9/gWoobgnctHUlQ4CFNKdCn5y44q/jT8Rmbpm1iVXsUjX3zA/IYr6JiwjdyZ83D7c9FkiOovG3FuCtJw6oekFtuiYzKW2wBLxj9//MV3Watp3HvaXbZ3xJ4j0t1lCaHw5nOrUDqKOP32qZiWpGHhBvbvdCB++D2MMYPslPS/uZe8jmYemXYvlrTdn5a0MI0o0dZWTNPglWA9mZF8HioowgAMbLaMgbT/l5KPalvY6FM489xoLAlc7GXFkthZku2Dz6ZpwwRcszPxeLR4uTikZKLooMxcTVHRSahCs13HIr4ZC4muBPFnHWRo4WRSu/PIiJ4rECtNRJaRUn4+xkGD4HE+9q5qxgo5mDi/ELAwpcX+zZuoducwbHwBlmXvX0qwHBK332YFPL2tjqAyk/MvKEaasXPCHiRkN1NnfSP73RY5I10959RbM0NC2bYgQxSFy8d1xL/vTlqPsFkvj5a60E34zngZSyroiDETRDzJ4J5qE6krzBs/CFUVqIqCGtNwcWhONKcLp9NFe0eQd9bsoTX9UrJmTsVoVXH5h/KJZVGLRXYsbuLstysIR6IkgiOWp0bLH/K1nqt+YRixoNEeWG6TrNoJFI6+whbZs0xU2nFkpNgXDrudVC1/hoaR1QQm3ovDm4YR8uNzpsdGa9l9QePtzWqqpR5wRefjypqKtOzIFmnpWDKKlBZWuAJd+ZS5Uw7idOYgTRNN0dEcJg5VYlqSrkAHzm3vs6JwMqnF80CV9E6Bq6i2d6/COo9hO3eRevaZDNqxjnK9jplTZiFEzFMmBGUH9lDXntzI6W4/ydIQlDfbk6UvP/qc/Z981MdSkd3CKwCBY8nNjDJ82KB4e7WsmFaJlFiWZNv2RvZqKpOHpdjLQpZEWPY1xLKXiopFBs7YEs9Jx5zHWsdT+NW+S2ORaBf/2PwbXj34FY3FL9pZ8IDhKT1xWTkRW/iwdNu349+FWkqoWHoH0MKu3CYYDsPNUeiGjiIFUT2MheTW165jrWrTim+oN0lRkw9ltXfciZKWRt4dvxhQwfco/j04anwcgmMvGM7vNpXz0Ptf9bt9mtPND88eg5DQEYhSBGREm+ncpOPBQ+agkYh0OynVb+ce4CdLO2g5uItpY0YA9gP/RlsnocwC9oqz+UlBCt9oW4nEYuxl30H0yijZWLWDIvwsf/UAezQnRZPyuf7bkw+rk3/VIBTDw5i8+QnPSzEOIFWFySW2R+atnfW4jRSmX3oOSiwIbK0vFa0rxOyJfdegd43pYW288b2f4hiRzVmTixIea++SEJusIEPPTJzCe+ObpTRXZnP5zXNIT0s8i/4mP0y4DWDb+moydhwgOK+QURPyEpYzIyMov9dFitQYVDSWvfIrOhsMph5nrytHTYu1LxeTfXwu581JnMTujuWLmDEul2tOG5GwzJqtzQQGpzDv4sPvVTeUvZ9S7FC55ltnJyzz9P2fohgmN1+e2Atx33PvEaqoZc7F301YBqBqUYymWDQR99zz49+Pjr0ADMOEtytoaA9Rsdf2EPV29wvRizUykC7MEXg+ZDh8mPEhFfD4hpA74+Kkv238ci1Qjevky3GmJV7j74a1Iwj1MCprAbkz+lf57Nj7GusrP2XY3CmklpzVb5loNIC277/oHDOG6QsSt++qT31w3Jnk3348Jc9lUr7oeY792Z191GNb/vg76lYn1/noNj6SXcp8rQA4gCvHRW5+rp3jJmaDWbE4HmlJ5BbB2cWZ3HPRtIT7OuYXHzM818+Zlyde5tj5s/f6MKKifpWWyr4exe8uuoi1tuuWG9TX+Jv5TZzonJDT82y95rqdzkgbVQzm+RERnIpC2VbbkHKldHHjOcexcdP77HfvYcaL0+3z6LYbVCgIpfLNkguYue1ZNCPa93r1anwtL7+MXl5O3i+OGh7/l3DU+DgEdy/cyTYRpdjt5NzReZwytRDTsmc9d7y+hU16mKve3hwvrwLLtn6Fgj0YVz+4HcFXqEoX83M6UcijvSvI/RvLebuhlWoNpFclw9BpdTgxn9vLxK5zSCnaiVD7CnONHtJIV4Mfv9JKTjiL+q2JZknia8ldhwMhyts+xGFBuON4vJm2vLOh6/0OGO4JEwhvtxVULUVBGWCl2pIDS4cbuj0VciWhRw6EVY9vYEhVEBDI/r3tcaguB13eKK6AhjQs+zxlz8l2e1KOJGPakWXtHmjkHXhwjprWgLETlmUeEVMgWldn1ypZ5xtrRH9tT+evz2xLWOb7gKyvSXq8gdpjpLkV/45lBCef1Os3tvdAHEIBDkdN3FrfeAYt3zbwj1inobuBJAu4jKU2EI7ExrCm+dABoSfOEQPQkRIitTPGaDMMBOIw2fojiPjo8XwkOU+nYh/nrFlncNasMf2WiUaj/HnLJ3gSZFi++/E1bGvqpMWy0AaQ4Df1KB3NPZRXhmTg3NLC3beeizczg5SiQlrq2pnu9PCj475PyfTz+duX+9BxsqhqI2PSCjl1UyUhZlKkNLP6+HksfvpH7P6sjJTBPqQ8loIxnUyaeS4XvzibWlcV+ceORQqBz+1DYKskzx11IuOHTWfXD58GYOv48SiWRAps3RwhkIqCK5ZDJ+OKy5Oe11H8e3HU+DgENxw/jH+sPci9l07ipDF9Z9KvDTqenWWt9kAlYPvuRh7aXEl09mmUnBJB330QvaIdISKYbVHWdo1m2FSN73rzoaMN3ILsDoMsVeXOoRZXNoBotzUKUm/pJ84ibywQpt0cZHfmarKONnlHpuga6HbHu+zvr4HswhDQXnYgbnx0dbTjjB7OPil+5mlCW7eCUFCbgygDDHaWTBZ1YKOhNYSCxJWEHjkQhlaFAMHO4X7mj0mcH6MbZqYKAah/agvhaAfQE6HfHZcx0FBmSclXnckHHiEZUPn0SGzF5iPIMSJNE2uA4FYAz6RJUF6O4k8sK+3QHLx77iDqalv6GEb2CoaMS3uXlsEYJZRwPwDhYGbS7TUPPMzOwizKqWDVxWcyrbyetIgOf4RK/7uULf4YgJs+ewgAtyMcl6EHMKwJ5Hp/xt36HBxmd1AnoEjUoIPZp6zEldbz/MpYwsBDDZvekLWb7TJG4usuLcuWxVEGcPPntxOMBhlEj7fosH0NRNmmx4jrT5+kpTNIJGoSjBnyviRJA6NRAxCHxYVIKbnk15+xPhhGA05K93PaMcmzxCpCQe+VoO+Ka+/g4zeeIlrfQLiuBaW0ibmW/Twu3fga1z12Aj/JKuOR5qFcv9/Fia71hBjGOZ49XFcyDqfqYPdnZQB0VgaAPzDzZFvPx9kVYaRZwo0X/CZhfdZPGU16Szslk6eBy4WwLDvhXDRKzY5tmOEQuWedfdTr8X8MR42PQ1Cc6SXH6+SddVVMzE211/WREA6iYjA6UxIWAkPTaG1QSde7CB+oIlqSgRg8iGhhBlsirVxRb+A2neREFOaYknTLydUj8piem4JAsK1sK2rEpMu9B7/iI9QZBWHEUjrEIv1dRQQppWh0lPQRQzhpeCbBQNiOoKdnVmSZBkRNutqbURTF1gkQKigCRdi6Ad66bBACPWxQua7H1etyaMhoFBwOnJqG0o8OgpqWhv94myYsP1ox4Iw9EjYTsiPDj56Eu2UjB8OvU4gjKYVwIHSqEHAqnHbD1IELAxO/fTy7f7+K9C43BRGFMnpiG76O52iQO3kit6IuE70jcdwEHCr51j8cqhjQSpHSShpg2g0lpncwUBbQKXMSLxV1Y/drjwzo/eqGZcXy1RzSaAbdeydvX2ezVExFYfWwCYzPzcTfvhrLPwzNMRgJzMoqY13zUMKGm/PHtZGfZnv5FpeaHGgrIqPjePxxb4akLbyFYFELkZaDfYyPLt1O4ha2qkkEqTjs2IQkBgpG2M6zoyXXApFCxuOOzGgURRze1ZpG8jYCsLmikRTg/MdWcsfZY8hJ8/LqmjKqOwy2xRyhXqEDTsxge8L9RGKTCqejp61YlsW9j61hfdD2+Oz49ek4tYEnAw6Hk5yCofH/h+WP5rvff6RPGcOIUrr+H3zyxzd46Y5bOPnSczln2hTmb25nWcROTvmHaWfid/ZP0a0vqyG3pJBIoIpIAA68/SbuQYPImzbjMA9Sh9dNODOdcx965LD9bPrxd2ipruSsn94+4Hkdxb8XR3O7HIJ9WxpY+MQ2tEOGBmGZHPfl7QR8Gp+cviDuMxeWxVkLP8QX7JkJdHjghltVBukFPHWgr3x1Nz4lyj0knz3mKx2c7tydtAxA0Y6FHLctMGC5qsLj2DPK1siQVidz1vwaj973d7X5+SybNx8Fq991/f2T8vnzrt+gxtYnukt0d7XdQZPrUyazde/34x2w1A9iddjS7mlaCFUbzql5V1Kl2rNWGWMBxImy3Z973QY1LPnCtOgePk8SgixFoMdmfPGi/bRoAciISaoqaHEHeS1LZVF+Ok63ihKbOJsBgwsUNz/9ZuJ8EUPu/hij2Id/dHp8zz0sFRtTqsMICU4R5NsHGrBtCBk/J4A/tvvx+RRevPP0hMeadteHdOgmU602VMWW1DZlB0qBG0VzoCgKg2vLcAmTrvxBOLo68ERC8RlFnG4tJWZslj1n3ZeU1B4Ey16JkJL4UpMU8OWwQQSdh7b+voioCmNGjOWs+x9OWOaZn7xOONBbBdUCLAY7FUa5NRAK0ggjRQgL0NUUlgiTF0SAoHRQpLTyFzMPXUhewuC92JUrSWvCsATBqEZLOJW/nPxzPFqPB8Gy7IE05z4XquIiqhuYYTeBkR384WwVSzpwO/1oigOn4sCpaGiqA00IhN5OINpIViQbgROjO/eLtGLBxBJdmhBsZnLDXFrM03pYI92IfZ4bPsgMxwrUVI315QZrmlRGFWl9Cu6p1gGFjME9isk9bdfeUSgUxgg28HJOPg1qWp9r7BcRhqSqeMxOsiL1FKideL1eVFXliiuuIC+vx/iqqGtm3h/XoAqL+UMbEAIO1mjsCWWxIP0A35m03564EEtu1/0u+n4nhIK+DYyaAtyjihBOAU4VxaWiuBwobg3V48DSFNqCbXy19FVaK5vJHenlxKu+x7b2Bta0t/KNQSMZnTkSh6M7iFxg6GGe+s7vsKIHuPmpf+BJ8fPnK25CN2vj5zFj3BTm3dPXC/LYty/B7UvhhsftTN4V9fU888AvSau141Cmn30+86+8rt92ehT/vTia2+VfwCdPbEdDkH5KAZqqoAjQN5fTWqfRdM33CXXVAWFGjZqCc9kithflE1hwDnWGTmdHK60KeEIh3NHtVLrqOHCW7cKUUtrueLD/1HTA1irmD/qcEekHyPdeTIo2oSfDqITWzlbq9+/Gl17MpOIRPSyOWAfXPZu0Vi2jOd+JedWZMVaJZR/EsuzPUuJ/cRHpLZuZO/4sTEMiGmrIP/cMW4nRtLBMk8YlS3hp/AJqjFyOcTYxYXCmPbPuZqJIyZjKVQgp2Trrx70YHH0ZHal7PmBS+072HROIueslgcYOhB3cTnvUw0nZJwLgFybV2b6eC9NtffROISohvcOgSMA2VaHFpQCSAyY4NbVPPIDsuTy9hK4Er3lNVhW5CAuLsFehTdEIOh2c0KUghZ0h9st8jRqSezUE4FaUuFhSj/HVcwp16RqGNNnrTuO05mryLKUnEC72g46uIEEt+cw3Xe/CETbwi1Asd4yJ7AoQcXVCeiqWlDQ6fAwyO+ysrHoE05JkpqchLSuesVgIgWUaNDY1kz4ilcwJ0yCmoClUB3ZyEoXOUIi2vXZKgKmjJvScXfz22h8279uJ7kusuAlw/CVjKF29O27gdL9Pa8nvKaS5ATcNaQ5y2w0ux8ET0taDCJs+Pm+3r/G1fherHAFakFR1pHP22CakDOFXd5CZWhhzI8XaqGGh7OpAmZxGNBwgajZhtg6iypXGvkg9U/0ZuDWVqGUQMUJ0yS6ilkVUSkwpcRga7UYAjZCd9kAosTwuNotFVVRWej04nWn4Qp2kaCl9G0HsPdfajkddTcSczaBMwRBDEtH7ep0yPG46rHGYRq+g3l67EkKCVYjDXciHP53GZ7sOkpXqo6Wjk3HFeUwYaidA7Ojo4LnnnsMwUgiFQhiGwf79+/sYH9Gord5qSoXqDtt7JNUINw37hBOKdhGQJtKMsYmESZxZJGyj0Tae7ffC8C14lBGwt7/MttHYCw46DlLpKIQhhXTpcOBpeylNAT7gAPvG/oLsnL6BqpOutd/XbLS9meOuh9D7P2DKRVP46E8PsWHnZjZffBY5mpvzH3kcT0EB0jT7eEP27N8fNzzaC0uYcdZ5HMX/PRw1PhLgxCkFFI5IB6A0WMundRbTzzuFyp2bWL9pE6dOHU2zQ2f7zp1sC7TSlJmBFz9Bnx3DcWZ1CXsL1nHC8SX97r9gdxNsrWJW/kZGZ+4nLdVkxoy+Wh71LR088ehiCsaMZsHpcxPWdfWTfhS3m+OuvTNhmb2vfo4kyqjvn5ewzIH5xzOubAfHXT+bay+4tt8yLfc/SYoV5NjT/yvhfta1fYkZ3MdNV/UwFto7W/hjxRcoIQNhgcNhu61H3z2XCc7kAz7A1n+UwtZGLrluIpmjMgYs3xv/2FTBk+29AuRwMiHSwWlaBz858zhU1U0wYjDsy+04PAO7nWen+3l5zuHqDDubO7nhy720C6jz2J3yiG/OYlb24cyYnzz4LKme5MslXmkySrbx1z/ZTJZAzW4OnnQeqRfcRNE3vgPAd9e9zUdBL+vmn85tf/4rUWmh7tlMKBYQqqZngbRQ3W5UdyqZ86aSfeEd/R7P09EGN1zB7LnjmfuDBxPWa/M3z8YaYM1o1DGTGHXM4YyJz257gkHKUIKDNFwNFqYqmfbz09hxxyrSTMgVnWTqzaQOltBuz/SfzmrmbLOZzWYhVUN1dpTk0GL5UKOFFNeVUmxW0YdenuWg9bggUkRwppmMGXIHXW3NsP1OvjfuV8waO++weh0pApEAs1+dzX5/I2WFf+bNk5YwenD+YeVqHvmY5q6xZN3+CUOAIf3sa+1jf2dXqZ9r/nhBP1ttfPzKag6sCBGJfMaU/K04ndmcPOWWPiJ2qamp3HrrrQDs2rWL1157Dechz5Rfi/DMaT8gL+/XTBhvP9s2df3rL3se2PgG5oRGhlx+ITJqYYWiGKEoZjBMNBDBDOm0vF9OrjeD808ahR4J4kpTEKqFYegYZgTTiBAI2rLsmZln4/VkIJFEwxBuz0JRfLTp9wMw/tRMBh03j3M1J+WLFxFob2NbxT6e+sF1aAiiiqC11l5O++M//kHrisWkAu/cfC9Rt5d7MpLHHx3F/w6OGh+H4LpHjufNBzew8eMKCr+fTsPmA+xbVwUUIlSF/fW2QNOfX3st/pumTHsw9KUYBGMu7JzcA3z/lF8duvs41FjwaK7/EuABRo6667AyPo89QOt68sBDYVnIAYKppJQk9aUDbn8K8zormHnB/IRlMvWy5DsBhDSxDunU0lIyuefRd+P/lz74AbRB6NUP0K5KLDQW/32WzUDQ3F8/QFVU7YaUXCa276cgWsfi7LlcGPkTo5ybKSu7iREj/otgbE38lXWV7F18sMebLkSvz6DoFgT7j5v49eo97PerqF0hrBgDwa0kZk4M1O2bgNabNtSdo6bXcpglQY2VydyxAa29mZARxXR5UCMhzDY74aDZDl5q6ZrQk2TrULj9qQgkfu8AuU2EwDqCYMn+sEvfzA428/0fPMnm3y/BEQtTqCmMolVanOkqBRfQBo35K0HCoLATHYNdx4xjdkaEtcEMOpQUcGRRG8piqLMztvfeYm4SIT1Y7YXkDJrKluaPAOxYqH8B4ajtmSlLtdlfr/xxId6RU/mvm6f3KSeMIKbSf0LIbhgRE4ea3PtlRAwkkv1l92MYtgEdClUwbtxD/ZaPROz6HWp8GIa9vOpQezxW/2xGVxF1orhM2xvkVFGcKo40N9ATzNz0wQFcfi+TZydO3Pb5F4uIRFaRnXUVgwf3vX77f3k9bbEUP4NPPg+A/GOOJf+YYwEYu+ZLSt94FcMw2FZneznuve46UrrqCafmknrWxVw6bDC/OVDLhV/t4zcji5iQktxbdxT/Xhw1Pg6B26dRMjGbsi2NBCtreeOv5UAh7lATlWcuoNDronzuHLwjRpDXthqtsYO1WTNJsToZxgEK/BYMa8KT3kZFs0FW/4koUWOiQRnukzl5fv+Kot5Y0rRIPwyUPpDWwPxPKRkoy+aRoM49AW/oIElX8yw5IP0zULgYf9sldOzMxbX2C6zOIMH1PfRN96hUfBee388vj7zD3Fjbzpf7m1lV76JQN8jVO9Ec9rUM5kyF8GayYss/aoye4gYi5iHxLL3YHoOiCsWR/utQFlkKvgWkt95KQF6CpmQyOu2qfstacuBbZmBnO+5Gf8VNehggrua6+PdqpG88kaU6UEyD1MzDZ+nx/SsKmmIObOwKgTlA4OqhaG9r4y+3/whnayPOgsPZFFZzA07yWcA0kJJoNIoEhlv20kGACClNTfzwzAt45rVXuSPXppTe/c2/JqWhdmNbhy1nXx9p+Fr1PhRflr3c5//zsn/OlDqdaLAe9Cg4FBS3m+zwGgyRfLAzoxYOJbkRp0dMUMy44QGgRxMLk3UbHx5PX8One9lF03xJj3ckUAwXwhVJWkaYAmUAym5W5pnU1K5CVQ830rLOvJTK/cswc6Hq88coOeUXfbYXzp5D4ew5tLa1s+XWH2MZBo68Eraq2WwfPJWPLzqfHI+TsX4P124vY8HGPZyXm8EdwwooHCBg/Cj+PThqfPQDh0uhoznMc/fZUuS5nbuYsNGW+fUHDE5bvITUG28kZ+FjOLMaKDjvx0x59wJ0UyXc6uDGlvtYnjETAsCyzQAoUvJ6Tj7HTbTXadVY1LllJhaWUBQFQwqievLZkbDkgJ6PI9G7HkibA8AUTiJygJlxP56PQ1HcvJQM18fURZ6j8R0LVQkgZTZOXwvhrhKMrdX4BnaIJESbbnBWqe2lcZak4tWj1GoKVc58cq0KTh5zDVMye5apnJpd31unl/D9uUP73SfAIz9YhtPfvzfjmOJRlHfB9aPuJN+TxoXj5+JMpLwoxYCDpilF3KuRCDbXxS6j+9NwdvXPeMgtyKepqgprAIaFAEhADY2XicWQfB3s37kDZ2sjptvLlJN7ROzSIx42P7KUYj0LByo+1b62luLCMEzatTAhl0Fuh4+LdrpY/Pu1XHLj+ZSuWMGL3twjNkWLXYUAZLuzByiZHC/vfAJb3ceG2vU85dXlhKb1ZVyNvTSAJgNwr710VJ5/BiU3v9qnjGFIHGryax3sDNuiYYCmZZGZcSy5eWcmLN9tfLjdfduortvGh9P5rwXxm2YUxfCguJIbTaoUKEmov/a+bAO5P+MjfeYpyEYVMMk75gbCra0409PRA0HWrd/E2sZWag2LfxSUwDXfZ8Hefbxw40XMf/JzmsvamfWrpVxy2nB+d9IYdh43gb8ebOT5mibWbOri05mjST80kcxR/NtxlO3SD3atreKz5/YAMH7ns2S0luKMBnj0hiK+90w1jtRioid9j3zHX8lWPgdgqzWEd80TmJCmc8vMW7j/sfto1UI8NtRemzczXTglzA4LVCEwLckXYVu7YE7hGk4dshxLKcSSjpiMtv3ydFTT5Utna8YwNhoLSDOtOLGyezng0R/dSFQRrJsynhRH70RnPUyMaG0tluqgddwk0l1em3khe5zUAHpTE7qAHfnjqSG717JDjx/jpuizHOPYxSbXTFLdWoyNYtekO2o9rX0dEnhg3G/49Vln2tLV0rTlnKWFxCLjL8ewuf4KPOIMUoWFJ1pNduqHpBSW01p3GqHoLDwF3TM8QaDGXjX/Kq8Gy633BN3Gz9X+011ngBtGjkeRBlOd1YcxUuLXJWKSFs4mhUw+8Br8QkvlB8cNS9g2/vC9z9he7KLtuOb4d9372hpJpYN05nQ8jhXMIMWZckiJHlf3ynX2YHXVtNYYFTXOsLaNEgGvrVE5sX4j12VlIRQFGahC+2wJrTd7cUy+EoTCddZEGkUGJ2Wm0LpyCTO2ria9w67b0uPO5pTPF/apf5G3k9SszHhiNYRCmTfEX0oqmKNm0Fqm43G78WYWxAMtFQTuyhpGbqljijaB5qoKVKeTjPyCPuentrZh+n1IlwsUBanY+0cIInqEXc0B7p9yM+PSJbk+gd4QID3qRQAeXEgkzlyFLKuGkV4nN40dw6QoHCudmO0R3G3NTAqswJvSSLuM0CQFZwab6ZBdrPS42OctwCFUVKmSUTOOwWYRqlAQAnaGvuKN4W8zTz2NDFd2rNYKSItQRzNef49R1n2Pup+eqAUVuhtvRjadeg3bAouZWJnDfV13ocXmb53v3sjBjCFkeJwI02DziYMppgbDlcGsyCqkw82nw79FrZDMjuWy2fbuGAzLhXZmUXxeYIvf2Z/d4RY6ljWjCp0Fp+zoaUfdHkwR6wF6vVdVV1NXV8/4CRPweLx2bIgQtHesBbGCzIwFpKQOi32voIQD9rKtLxOpaghVA8WJUJ0QewlLIh1OhNOPqRu0P+lEmdlG3nHT7RwpqgOpOrBUJ4rTgepwUH77ckozGjj9Z/2ryQJs3fokjU2/Y8L4ZeTlFR+2vezj+zngeob0vzjwblf4zs9+TWmJHT/liYTJCnRSENVZn1fE8abGG6eMx7IsfrJiD+98sp8LTxzKIwt6Mtcuamznmu1lfH9wLneMKExYr6P453GU7fIvwvR2YCmlpLcepD5PR44SeDMN7mi8B861y+hESRe2Z8RIKWJSZwUTxYvoXQrn1Rcw5HubGALcF/gNd3xxJ0ITTAtKNE3BAEwL8jSVqKawtnYGme5WZg+qQ4gICiaKMBAYOJwBsrQ6xrGacjEJSV6cWRHjtFBdUIi3vZl2M4SQGs5DZ9QSTM1BY04OgZQ0ZDiMMyY00XswNlNTaXO6yKKNUiMXtTvKXfYYKKvEdNJkAE+4HjcOhOwR55LYjJ5OMlmuT+bTzRl8lF3R7zU+YeQ9nFKZG0+KlSkiXOb4CBrAJTPQlZHojTFtCqtnBtXUIJFC601l6VO/uNqUFKTkfUnQU8IOy9trW18mrmGZOFQTv6mTG4BJoxKLcAGENAVfxGJxsFufoOdaWyhoxj52N28DS0MN9eHdHALb+Fi4U0HK7lRyxD7b7zglBSOrkK+vBMtCsSKYPkk0p42A8VdA0uiwY4+WtXQiJsxm68TZfMt6mnKGsyc4ro/x4XYpWM5UOoNGjMFkV61C2LPiNUYrhdkazUIijXIsEeMqCYmeH2JlnsLjz5WTaRgI3YQD5T2nIyXuji5MVUH3eEBKRK+XS0pSUu3llp1tgsaADmjIGOPHYZm4LY3sljpcjoOUB/3AGLZq0BSJEE0DPT2Ndu1CPt1wLcMxUKJRUkJdDFY7aI14eEkZhCksXNE0Lim/GNsE6wIETucw0kLZbHCshXDv6BA7xwudoT7rWr3vmK4oWEJCc2xpzlAoqfOh+e3uM9RRR0RxkN9ejewQICXVzKKaAsywIIcyJkd3cv6eR+lJIij5yrIDzCMfVyN6hWR1HzuCBLwMdm2jZEtiWnNvlHR/2P5RghKHJ6g8EtTkudg1OgUtkM8wHsRan07t+v0JyztQadu9jt9962U+n3UaO8dOR0jJrPJdjGmsRlEU/P5yJkyEbdtPZPsmDYfXDUK16b1CwfJZYEBomIJrp8LMrlZKY/vfMn8qqW7bA5u/ZBOfd3Yxf9EWIrKV1pqVlLsfYdvOcaxotIOeBeAFfhsIMmfNVlYYDzJ69DBSx2XiGZvdJ63FUfx7cNT46IVIJMKnn37KunXrIBeac90ck1XMrPPupHb3nbAUTK2L2lNdzD7hJIx7HYSLbsB9w8NU7FjJJ/f/ik7DzeS2VXCevU/TUDgts4unftR/rgiA6ff+g7T0mVx+5tX9bl9Xu5bOXd/i4ckjmJw75fACZ3zKkg0b4aF7mPyrh5gxsv+8I58v+pCla9Zz0Xe+Q+GQ/uLv4fn3lrJ/0xe8+YsLyfT1tzZ6OWPu+phw1OLHp3pwagpOVeGk4RPYXldJKGricrj4ZG0TojzId3M76A7ZVEQs6Z1QEAWT2VYbYcx2e/C5LO/H8SN41C8onXsJyCimGcGrb2f05sV0nHoF3z6+f92U3qhc/z5L7rudeYpg0PQR3HvRewnLXvTMFag4eO265wfcL4CSVk2RgMpTEks1n/10M3ur0tlx7zcTlnn+w6tRaebKsxYmLPPeS+cjpWDylrUJy/z4j+sJtUW4597j4t9FzUdZX7eOWQUz2D/taV556q8IRfKTu3/Z7z4Gb1vCh5t+zONTH+b4yf3nK/nzs7fwd2MVM9au63e7lJLSseNwZWUzYeWKfsv4dxyAF3dxUYaTkvxCJpRkMH9eSZ8yv3/pA5r3VXPr3bfx0NINXOU0uf/0YwB4a/nf+a6cRP25f+Ok0XaAYsWBT+l44yo0bzpf3LgBgK3b97Fq60EGn6Vx7jnnxvd9O4c/XytfXcW25VGu/M1UUrP7Z1Gd+NwFNCl74/9HnPDBzHI+kN/l7OqrmTZ+DC9OvpttBy3K7rPv+ZQ+e7gHgPM/3c46PUL1GXbd+8vG05uBsm7t68z6+AZqrlsFg26n21qUMd6yjAu1yD7/97z3fG/T78MoQiKlEXuZuJ5cgNS8hK95DUwdaelg6mBEkLH/vW/+gOyQh2kFP8eKGhihOvy+DBSnBaad7HL1h0vA4WPQzJOQhkV7exvOQcWoq0oZ1NnMYCe8hYeWtCyyZQTDMDDN8VSWN+NPrScjsw7DjOJy5SOlGT8vyxI0HzeM4373IQ8Bg9Zv4YEuSUVbOxPz7Zw+an0Iy69x0DIIetLJyM2DSpjYvpMDsmd5UAJz2st4sv51ALZXV3PCujqGXjYa//TEsVBH8T+Do8ZHDAs/fITWlk+RCIYNA2ckQuHuFkZV5RLY+XNSMWlreYeOY8vwBIewZdF7TKYe2bqUcGs9Xz39RzoNe501WO9l85NjQVV5Of8ixmcOwAzo5WpNjr6FpCXjsst6RxsA7eUb2N68GsswUYTGiKln4vbanapp2PVQk6x3mpZdnd5KiIdCzfsHVF3C7z/sCWr8FasPKyec7dw1/oyE+zn7qUWM6UdXQwDT1tza5zupgitv3GFlD8X+P9yC/uQyjgWOLZWU7W6EixKXt702Rz7rkRYIJfnNMi2BInrW8s2uLipvuBGzowMsi+xbvgOKBUegTNqfrHZvBEOtFMhdbNrQiGkZWKaBZUbBjLJ6zxa+0D38dd55APw8quPU+r/e0JOErP+KDHCNYnEizpKShEXSLMhF8GGrTqi1Bt+uGtbOLMLv7RHf6r0IfOhj8YdQNrjhQN2+uPERfedGRoS62DNocrycqccChgcWED2irLHn5kzh2ea9/GH2s3jcfgSCfc21PLTtBywc9DwLLcANvuFupLwkIYvkSNpZ79+On3w2HYt9HNz8DoWDJ8XvgeAQUb1/BVIiNB/e7KmJy1i3omqZOMfGAuP7yTlX9/Zj5GRkM/qKk/t8/8ttmyhKT+OOE2fz2SdrKMjK5DuXfSO+ffc7g6hK+xkA7i4/c+avisugR8MNrPzyWPy9Qkey3S7oCuNQe76svqJHhmDaZ+8iHZmsziyipKuJIT/4HDVG65eWSfXdx/Spn1cR3LBvM09PPhXfv5Dq4Si+Po4aH0Bd3ft0OZ4gmCVQhU1vdKkSKw2Cf9KxDIk0BYGh1bRPCuIKNiKE3aDXVZisubmvel6DMzsmeS0xhEqTmZhuCXYnYiUJvRH9LBdYwSjXvbOZcp9CVBPMLd1BLrD56Zf6/Hap62XmXn4mHn8mqw/WE3I4WbV8Hfl5g9AcGsuXryBqhdEcThzCSafRjCIkziSd8dSiIWz23cWrZ3yAbli0hALc8NwOpOXlu2dGGJFVyJ0rX0OKUuBbCffjPzaXP22oZfGtx7NV3064bjP5qfmk5RXbioqKwvcefoLvK+8xJrcZLT1xIChA5SsPoD+5DHnuSBw3/Bc7f34b7shAlFD5tYwPPRq1Z3xJYFkCRekpE1y3ntBXX8X/b3vjTfhm92JVYnhSNMQA1NCT9Oc5QXwICRwo7476KRTYo8W1C5fy0vmHBysq3TEER9AGE26PDQZqenrCMp4ovE0K3kmC6nEjOOfVjfzx1a3ceW0vmqXsSbcmpMTqHS8T29JEz/PkNKOsKRrHKZf3LDN40u1uzVswsHEXz9KbhAnmiwVEHlM0khS/fX5zhoxhRNYbNAbbsSyLN0s/YWvXW0RNE6ej/2716zJbfW4vZb5Cwu21Axf+Z2GZ4EgiJx8vk7wPM00LVft/7P11nBzH1f6BfhuGd2aZeSWtmCxmsCyDjDFTHMccMzuJnRhjjO2YY2bLzJYsW5LFzCwtM+Nw0/2jZ0naXTnv+yb53Xt1PhrNbHd1dXd1ddWpc87znCPrEVUFKZLMLmRAXVUFC5+6A0kEURQ40GIlKWMsuXnbCEZ5+WXZIGLVOAzFT5PLZKuN8XYhlNTIAuqjndUkyE0IgCQKiBaJDJeVmYuX8scDX2GNUnGlKlQ+NpKqAX8gVZOILnydDLmE61PO4oXmd3jkjGweM0ARPbSq2jHl4z8sx5QP4K41D7HNe2TE9QXNColDEnCffCrRY07GUbGCJv3vjB79Iu7M0Xy95WS8AfMFUWQbaBqtsocf0s5FFkVEwKvrWOT+IXeC0O+436V8dCu0cvUyFqUlI+sGqihQNnwip7WVMFFaT/zQFiZN+ZQdv7zPJ6UG/9DGEgi7YKhpObCu/IbdB3d0PwGxlkSa21oQZBFZ8bBp806mTR7T6/U4xGgEw8aIlC7I5PtXWVldXMTtM05GFES+bVzPxtL1/d63wyYTtgjkpHkAD+QcCcH8Q/wOJrQehAZQX5tPS7yZo8YQBHQtiD1gIIeDhP0G6s9R6NMzGfroF4iSzEFnFEKw/cgTd5Nfk1m0u4TVMN5gc79lNF1A6Gb5kONNkiPnlMnIsbFEn3UWtL3C0S0fR5+tprAcgIYbdiHLViySBVmWsUgWRMnCU4ic++xsHky/knumH3+U2nqXq3bsosqdR/7uQlq+/56YBX27EPtKogZgqOY+PQTDRyWR+4nE6wdr+JOuI0ZWu+H2BqyYE4yIyToKsHHPCg7Z03nKWc0lk85A0RWCahA0Be2wXCxGJ0Lo6O1XX1oMZKP3c90diol+WMrjqdldGWS3Vh9gpxfCmtq38nHUqzlSQpYoLOH++/D/SoyjKxa/poyigcV2ZBlJVZAinCOqJCFrGqpuENYMNB2c+KmoGMF5VatQkt1U5SQT1JsQJJGkcBIDtx6gNrrLqhXTFMChqnwg2jDCCroQiX8LgxIQ+HTFZpJPbgOgGpkFGVZeL/0b2cEQddbJfBt7J2U70lg53IEhCIyLcXFLTvIx+O1/Qf5Xysdjjz3GH//4R26++WaeffZZAGbPns2KFT19vtdccw2vvPLK/+ZU/1b58+x3OOc701c7KXkMvxtyDtetuBd/AIxdNfjWvIGPN2ifKsElQARmeLP/BkiCmZNSQRBpKG5jb00bNw5Mw2aXQRJ4e3sZdYEA1/7zZyQR0HXCoSDuKBeiYCaqtbbFIhUWsfrbL5FkCdkiY7V3fCzU+CtZE15ATJPCQd1EgHzWpkI8qBGzvAhUxQ2nxBMiJ7wYS0sDeSNOZKscIK69DaO9HQQBr8NJ6+DTuCI1BlVXMQyd1Mwk1n76IzTldLbJj5+/RuaAO7p4I7shAFSlBcQA1a0HEQUzx8iQJBvDkkfQFqxHEiT0SHryllA7mqGh6QYGGrqhoxkGuqGhBltINNrZW2Ku7AzdDHDUI8GQvoMryW/dSBALdhQkRUVEQtBNX7a7rovvwCZC04h4hr6yrHMi622pWd16gNZgI01GHKJkoU0LEOWXadh1dPI0gCjVhtsRS3lpUSftfEfeDyNCix/VGkVAj+Xn8kaz/eIyEX5e04lOEgWBrH3rsId0ApWrCYYkQnLiYeZ6AS0YwmkYtBUc6Iqt1e0Y3XJ8OLUo2vUonF4/gq8aoaEKPRQkGApghIIY4RBiUQmnNz7Olvg2tu4TujWLiZAoayoB4IuGnWzdYyAJJgxYxPz+timZBfsM7lhYQvXCO9gYHd/ZFyK1IAgCDQMGM6C5Ce/3hwU7Rk6oVDVQSiy2dhee9RXMTvZQXN3MrW9sYsQIA5ddwNdQiQzs2rULQdcJqzroOs/v2wPxU8lvX0nxI78jQVWwGjpZGKzzaXy6c1Pn6RoqmwGZlv0qh6y1SJKAJItIjiZsThlJsiBJMqIsI8o6CCrhUIhwKGhagQQhgkASTWK5SL2qph5G8BZRpnS9s02DqorDYkTa5DAir/+B9hGwxRAVqP/XD/y1ooXR/S0oQT8Wiw1R6mX1b+hg6X8BFdYELPbelQ9LxPKBCKfn27hkZrcEcK/Ogaqt4MmCq3YQfxhlQMPmIT34idJKW7msbBVzB03BGmXHEx3N0FmjMcI6+2vaCGsSvlorruQwbHbx9E8aIUca+yaeja5Hk/T+p1QMu45HJg9n0ISeWcuPyX9W/sdQ202bNnHeeefh8XiYM2dOD+UjPz+fBx/sYvd0Op2/Gjb734LaKprCe/ve48VtL+KUJFqUAGfGhJkdpSK2gPphIvaT65FTVAgNImr8LZz2cmQ0sZgvh2AYRCsC52h2ZF1A1GGTEKDQGsSQdHQEdMMkmDIEsYOHkRubOxAWfccB6AK8sCCaVlfvpsEzf/mRmz9++6j3GZZlFs99kqhwf5q+wZDzrj7yWDP4nLVeme9aj75S8OhQmPNen/svWLuEGKX/9PQAKdRyLR/ClBvgxEcI/vga2pK/43JX4/enUbsmjBoQyV26CTk2BoD28jJW3XwBsmow/xszHqWgfh2luy4BYJ1X4uNmc1BU7NO5Yfm5v2puGO2QyLEd3Zz/XZrM/SP7Zrjcun8+abVdRE3fN/+JktCEHmWuTzmr12NrQi+gGjkA7AloFIS6VuSDDn1KZuUvPcrffoVEeVLfd6dKiUhaEwK9u6iakx/g4/seJ67dXFHOefmjPus6c+3PpEQIrQ4XzRD4IHQcej8WnylyCYNlc7L9cOIJBC1WZMAfcQ0UrD6JNtXGW+ophLAQxMrP2jiautHeOXX4Q5u9h6soKm0bGdNf6v3+g27WbzwzkpunIxmNidLBMKh0VbEufUuf19xd2vc/CEbPd0OIUOyEBrrR05xUnzL+V9UFsPH1c8lq2EHKPQd/9TH/ktwf3eNPzRBQkVGR0AQJFYn7B/+BldHjsIkgoSMZOhIGMjoiBjIGAzfYyK5pxm2zIIpGB8Iau6+Q6NSNxGVHszdksEsOkuEOIosSsiCb36KMRZQRNQlrGQy2JZqKoSQT3vEZzuwhDLnZDBI9sHgbC9d93SPh5PW/vYbEPBP2fWjumYjuaFxjRrNHL0TdUUtCSwhHXWGn2y5h4XckjumD/fGY/K/k3w619Xq9XHzxvNfRewABAABJREFUxbz22ms8/PDDR+x3Op2kpPx/V/SwRbLw+xG/Z9GPG9mfsAaAZFlHUwW2fzIc0WLl1op9UAGwiaUHb2RK4lCmu32MzzvHdAMIEppoQRdldNGCIzaT+kX7GJqeyYMXmnlOvvnmG7Zu3cof//hHbDZz8nvx2mUAXPfSXDRNQQkGCYdChPxB/O0+Nu1son5FiKvj4xiYF9N5zXpkta22NGEMME37NTffSlq+k1hJwNA1KsISipwKCPiWbSTti7eZPSkBS0JiN4iq0en2Kdy9hYYiN2L8M11gRF0joDbz4L5nCEbe+mjJoC72OgbWFjKrejeD7XtxaiqqKBC0idiDOmmqxo5pDUiCiXCROlfTpkuqoDSAvwTGzD0NIbLKJsI/EaG6wL/uHSraIysqNUjgx/exrb6DsCrTuN9F4z4NLWQO9h2Kx45rfo+0fS3ZIdh8fC5VbSXYZDv1bSY0MGDYiHPnc/OQmznpTfMVaEotwTGy/5gSAJZXEJZk2s7LiNArdHAv0Jl8rP3HEFlBgydSkzuZUSNGkYiVBEr2jiMcXYPTOpCk+iUkjY4nb5S10/9mAHxvVt0w530MQGopJ27bHxEGyhgRtFJoSQluXWf66RaWftyMkTeY3IfPQJctPPHz47QIQYKxYU7053PX+Y91AEt7oCGWNJRwT5WF+zI05qYMRNVNB4NmmEDUAl+IV8+6iHveNa2Xa3LiOuHe3dcu8wrrsI8Zw3U5qT3vI/J7V3Ur7y1r5ezB0VwxdTCqZuALqzy4di37KjTeumIk363YDGVw5plnUr18FV+PmUF3vtXnxUv5KDSBNlz88/cmN8RcwyDs01E0A8UwqKwO8881Tdyan86U4Uloik517XYAUqP/gWFoGIaKrmvUNS5Dtv/EuKEDwBBNC52ho2lmQkVN14kuc6LWiUxUB2BBoio1gDujJzKmeH89ddXJHDckB1mSsJa2IrWHMQB/gp1AtJ0VFpWiXxFk3CHbVr7OxIolrJl8H/+u0dRv2PhFH816YSynjk7D0BQMTQFdxdAUWnytfJY0H12UuEE/gG6AZpjMumrHtw55tW4CVheyJRxJJCigaSLNxkSyQ3uIaz7AFS17+EtSHivQUDFQAVWIfAMpNU6mb0+ikqpuzEJZDLRZ6HBwDT5pLH+aNRxBEFj63vesq9xO6d6iTuXDUFUkTywpD9zWo838je0E1q+j7vabcdv6Z/A9Jv8Z+R8pH9dffz0LFixg3rx5vSofH3zwAe+//z4pKSmcdtpp3HfffTidvZvtQqFQJysfmJrTf0sONXo5lPVbbt6hYUPhld2nIEtuTku3EKOqwJLOsg2+UTwZ3E1GewNa1U6ECNNkRdCM/Iu3PIxDWk8rM/AfcLDvm0raFAsHCkz/bXdzrGEJYY/W2LV6NRabFYvdgtVmw2q3sfarzbSUpwNwXFSYOcm9wAFT4tnW0GD+nDKFwWO6UsJ3NyweKmtHBYZNScGdl9FrGwSV7TQUCaRqrdTXbqBcCPNobQeSReCczJFsb1cpaC3kHHUY5z3zDi5LM4NON+8rfPNGrLGDaf7ht7i3fMOY/Hl9tvePh3awvrSWM2eOO2JfWFGprG+i6FASFe1mPh3UIOrGd7FqApVFJxI183jcwwL4t+4gvH81VX/6O3F3XEHIsZr2R81VfAYH2be5Z6yDIkbhsMZyef4cKlgFQFwgh4zfTOdoUrHRLD9m4uQ+yyzeuAWHX+W3Q1L7LLNltY0WMY2Ymv34iWfC74+k2K9ZPAnRZiNp1mnm7RfuhG0QMyQR2zRz4t21ugqrBnknzGDZh58jJ8Yjj57Nxl1L+CapCQERwRBI8qWTFNc7sZI70IohamS4LAyJPnKaGxcHr55wIrfEJ/L30YMYkHskIRQAhXXY3B6Shx+ZdA9gl14CtBLjsTJscGLn9rhdKpKkM2fAMFZ9LKBjMGbMGC5ua8Oz6ge8didDCgZRHL+TH6Us2jDHkncX1/DwWZP4y3vbWNV2mLVFBHeinaFTzGcQXuOgKSAxaMTJWGxd1sN168rwB37i5HMuROqDjXbNl8to2aFyQnAKNizoc5PJmpTfo8zS1k3s393OZWcNJsrjpOKeVdCB5GrUybhzHI0/7aNUCRx5gl6kcuP7jF12OwA21/+OlbU/saCwScvnXX0WYoPKjiofjUENDZFKIcaMpxhittclk08kxxVzRB2+oMLbX60ifVwCp0+PR5QEREkg1B7gg+caSJ14DuknzYFHMzlr4Ak8OP+JXq/lnY8fp2H7Km58/0tkScZQFZ7+/YUUNtv48qVPccWb/U4QBGLibGwvLiJVTCMtZSDVW8wxosUfgn17iT5QRuzgrn7qjHdjnTKeOqDp7XdI/vOfCO7ZQ/1zz5P9wfudCJtj8p+Tf1n5WLhwIVu3bmXTpk297r/ooovIzs4mLS2NnTt3cvfdd3PgwAG++OKLXss/+uijPPBA7/wD/2lxOAyuWhqkVDqf99whkpQG/qaJDLAmc4NV5ePQYyQJzRgI7NTz2CGbron60bfTYHUzYlMXB4VfzMXBek6MTG5sXcJLXIqPBGyE0Da+CtNv4POyasKiF6EhntUfdqwBuks6QkIZ744YzhPxfbsohEiQW3+Bc801ftyYCa36ktKd24HpVLbczyFD5MU60+pwYnIeMzJmctKQ67ht43scai3ijKyhNM+YyZik1wCosp9IWuzgyAX9Glih+X3nQ0/h0rzo3RyA3RGm8RF3gLJjGW6hCm+DjTsn76ApsYyT7HPJaIVx+6H1i9exThqNT0kFKpDbx2Fkj0GwyaiagqqryLKL1oYNdDjgv5hk8JsN/3cEQ1/VNtMQDBOnHt2bOap2LaKg0yAMpzfVvDvnQ+iNW7GVvwmA4Oiit++eRcdAZH9bOvtvWwtEcQXdBvmELp6Kw0WJxC7I/SA+BjjsfJM/jBF9BCGbInSatnuTVI953UOTerqjNJ3OAF17ih1/mdnPZ86cSVVVJfv3H0D3rSU/JpM50k+otuU8HTqdNVWJzHthFTowMT6KeUOSkREItYYoW19LTrfkaqqiYBgisqXnPfoDbRiG0KfiAeB3mP2vLlfBE+0gf3ROn2XFSMd1jE4ksMN0HyXdMMbceXSAU6dIB77v/D10+T2saCggZ/z5ZGeO7Oeof1EMA4ugky80gWHwbpFAOgaZ0VZkAdSaemQxRCHpuEONZDl6wdgCLY2m4teyLsi76yqP2G9xewgGW7ABorXv3DKhiGImy5ZI0jobkt2B3lxH0cqPscf8oVtpL1GMQQW+fH1P1+bxfwRg89/3cdUziVhcXX1Njosj/soraHz9DVq/7sb9o6rwKzJrH5P/W/mXlI/y8nJuvvlmfvrppyNyB3TI1Vd3xQqMHDmS1NRUjj/+eAoLCxkw4Eg/2x//+Eduu62LYKqtrY3MzCNRD/8JSbFZeeNkC7F7wgyqKmB+/c+87hnJvPhZzE+LpqxlIO3F35DW0sKZtSsgkqIiZceTnSa+dNtpGFipSBhE3LW18GgGQlwuXPYtdX9/hSZbEytTVvJhocaK8RdR8NzTBGJc7PccYH5GNKdOu5VwKEg4GMLv96GFVJrj8iiptRwxbq1Y8g8ulqbh0Xw8g48sQOsn54YY4e4w+slI6nTkUy8ofLw/iQ0OL+kBD/eMu5vZk7rImsz5UCfbuY+UiOJRMfIx0k4/bPV+lPm3JSCiGyIuzYtqdZM2aAQAfkVnY3kzqqrjVFr4PWZODItuJp6LSgvxSGUz9+QZOKI+4sPxFt7OlHj+FY36u28kKsOgDUhOP5EhY0wYdGl9Gb/svosMYxOZQKk0h7e//J6/xaSzdJzKX9UmLHv2oKsq9thYYrO6Vk03/elhFqxexrq5MykbOgdNtvNOH/d018ZCltWobIyTqPPVkeRK6rWcYBiI6AT0GOL/srxze21JFZqiEJ+bYXKKdGhorea9B497CtuoKT3bOFJk+tBm2rytWFMSEUQRURYRJJFlmzSseX37XzsQJf0pH/rRHub/QpTtP/PJko18teNJsjz57B8wnAcfvBdVl+hIFvD45eeSHNB5uKKeseJbXN/WxqO+45icMJKHzjublHgn/jo/5c9sRcOgXLYgal3XrKkKGOIRvCnV1VUkJx8FRiyb+wedPY6EhN6tEJrSs33iLxwCFw7pWehfaMLo895k3U9PYc+ejLjlbY7b/SbOHS+yauC55M6+mfTkPARL/1lzjya64kcEpo8cSMkFp/ZapqG1hRFbS7jJYesK5D5MRKvKpKgPCOaPJWvASHTDQNdM6hfRIpM2YzLNzSY3qdSP8hEMB9EFo4dV+KZX3uGzR1+kct96rnpuBrqqU7i3Ek3RcevWLt6ayCG618uer1ZRFEhDsh0J/U28/Xbso0bRsvBjfGvXmscEg52InGPyn5N/SfnYsmULdXV1HHfccZ3bNE1j5cqVvPDCC4RCIaTDoqUnTTJJXQoKCnpVPmw2W2fsw39bZMnGmIQiRsav4qSWpVyV9kcqbOmsQiWYbwVbIkNTpnHD06alZt/CNPalxOC+9884vvgT05NKEQQDgRBZjbspKFhLnqYQqCkisN+0FMWF4kj2JaDKBuWHthKIMl9GqyhSs64S5SSBqPhkPtn3AY5Vz3BpWzs7PXkw9i0Ot2n8UlOFminTJEazr640onxo6I1VlJ83j2CdjiBBzPShJL3wJXHpbkJAfxZGf5TOG5PuQtIETpIm8+CVz2Oz9lQ0RUQzZqCxAICDp71F/rjfHFbT0dkzPt7rYYjRgACMnjyDc+ea6d6HvL+WYLMeCSqLJWCRjojDLUiJoSgsUdQocYJHYfroaHae50NqCKDGJpFIDc0eJyV1RbQHQ2zffgUZUbWdx78cOpXyGNOdde8gO8HN5bz86drO/TdedRXx6ensGzKU6yLbshZ+DHzMJ/POYv+BNnJvH4Mtust9sLG4iRPXNHHfyFgWpVlI2rSHnbN7Vz46xCG2YESgopX7C3jzkRtZOaaB6niFl2UvM7z1fPv8dGY35WCVZCxbH0Pf+hig41OdVDQ8hYqN+op2ht71+x51f/n4YzxRnUC1J5VZpXFU7lzKw6OOhNuGdDPQWeqnY2i/cuLs7Zk/e+lv0MJhdFFiYPxcnljtZdSQBPITTZfIw4vMGKvBB6A2q5HyhCxa7NvZl1pBWkMWauxQEpobeffTVTT87j2KLQLJFPPPxaVck7UI9ckcMxQL6JjahjskfErXG6MKhxDlIzOxZqSnc7Sk0R3SX2x+faFZd388bT3TAPQvDpuDKafeZ/4x8gRC4QBblz7LqC0vEv26SalffPlKcrNH91NL/xJub8EO+P19u4IE0RzPLf30DVUIMT7qM/aMPZmsCbN6P1ewFQCpM98R1L/wIg0vmAk77aNHocxOQT+M5lySZdRQEFGyY7VawArDxx+Ze2n7njrWr6qkqaQNdyANR7gdsRfIsyAIeObPxzN/Pt5Vqym/6ioOzZiJ+/i5pD76KOL/I3PR/z/Iv4R2aW9vp7S0tMe2yy+/nCFDhnD33XczYsSII45Zs2YN06dPZ8eOHYwa1bvZrrv8txPLBTQdx0NmXMVrUi6P+B4BIDg/DQSBO9/9J6es+6Wz/P6UOIqSYwGDKDnMyJgapiaW9ahzTX0W6xuy8WUPQXdGcbhUOitZn9w/J4Yqp9CSfC/RQeiY2JtdXe2TVV7OO3+7i3abC3fIB4DfYqPeFUN6az1eh5sYvzkA/Dz7IXzuxB71G5GAyZWpL1Aea+assYiWI1QIQRAI6yq6oREvpfF90SYMICRbUAQJRRRRRYn4cJAoLcji8WMwMT06CB3ZaMzvH0qn8V3JPGJlxUw6p2uErXaCuoQhgGX0Tzi8P3FnSZjfGjWUG4k8pl2GkbiHVTF7elzXVJfCbYE2Bhf6CNhF1k6MO6INq73JpEYUkIuFzwG47qOXyGqspDJ/JGo3noIJAxbhtreReN+Rz6IwazKViaoJYxCFzhnFwIQyVdth15BxrB0/F1HVcQR1Llzjw6mBLgKCwL3203rU+agnC3GHxs4cgZ155kA/p+w4ntO+OvICusmLNV92/vbLIBrmx6ZphHzf8FXcUEqd2UwNayw7LYvYyvuQlQ7SKvPZ+qJPxh9rKo8ufJ31dVHbCXiDNrDLSGG9EzLcsVuIzKphm8iIgkPMqtnfw+3m3N2THr4j2WKc3oYkiES3tvDbvYuYUHcA1Wwe1gxz8tyZdu7+xE5ewEF8RVcekfo7FZRcg9ZnLEgTb2WcryfzrS6GEXVzJRs0zL4tOmoJxh6ibtR7gBhZXYsM3FNPRp2PCkteV4I2zIsQIsmPwqpGm2rlphF/RdOiOW1HC1GhDnIys7wWElCFAOG4CkSpq57O/wXYkZTNT4MymeTvbLpO6fxt6KC1IVubItu7kQAJArqmcXLNEq6rMBWQpePu5PjT7uXXiqHrFO/dSFreCMI1BXjencWX5cMIyXFIkoAoCkiShCgJSKJEgyOGu+feAMA8PYAsCghelZiwDXecG0kUcQUKuGP9hfisybSkXxpJSmcB2UqxRcKW5CZYv5Xp297g8bELiMmZZSoBdz/bmUlbMGDLvCQy8TP/hNtBEBFFCUGQ+OW9LwkHQ5xy/S2ASHxyHlERuLeu67zy8jaMXa0oGPg8Ep7GAwzf9z1z135z1PYI7NpF6SWXIsfHM+DHxQi9EKUdk18v/za0i9vtPkLBcLlcxMfHM2LECAoLC/nwww855ZRTiI+PZ+fOndx6663MnDnzVyke/y+IQxL5JeUTGku3EoyS+FYSiGpsZu/D/yBksZJfXkzIYqMuaxCZhbvZOSDE6pkD8Fg8xDtTaIhKIJSdRqo9AVELsf4vt9AYcnLBrdcTDgbZdWArB1bt4Yw/X4XNGc33Gz7h80CX4jE8ahxnDcinra2K54q7+FJktYbZjXuIcQ6gc6hq95HbvhtZV9msDeCFUWcxzq0S75BQW4opmDyTqJY2fFWNCNYodrX6CDVC/YhMPE5bZEwz6/IpOkFNJzZ8M63qN1g9e2jwlyIiMSh2YBePBVDlq8aneIlKGMu1llQu+noVngYRJMPMzioa+Ix4SDIQJ6ZEFBgxgteXECK/Z6SrqHoFmpFJdVUVhggN9hhOkp3khQtYUX+QAcHpNIjp3K8pvB0yLSNJsV90NsE4OZ0taiVrfRYuPfgksXorXs8rjNhbzeLkaSjObNaXWilvT2e+rZ3UUW8D8FBhG1NLBfYZNqSkZHRfK5VWK6kZ+5EkhVQhFTGcSug+AU3VOFSRQ2P5mehKHWrwF4YPMVecHVNsxyRkGAaBA+VMK8piaLU5gVh0SAxCIN2OlOI086AUzibWvpcEoR4Jgws+8xNssjKgyqDZLVCeKLA07QAjyv/Kua7P8FgrucZ6vqnE6apJruUDVdCQDYlglgPBZmaS1UQBo6GOce1nkRvYyRYqeXvwIACmRp+IDSWCwjEbsbq9lgp1NzPcFuLt9kifiKRci6Bzvtluoyo5hckWO4puoBo6nZyjAuysakUC0iqKGSdupTy1i1bfmHMqxfVboaKYUlcKsmcbgtzOqPBQLJINS20NDjVIbWosJVGx3HPbI53H3nUbCLrOsuu7cumIS28mbcfrtMy4kJ/Th7GtbCkAkmDwm2HZuJQoxJ2pBF06Slw0hqriqU5G0q04HNkRtIsG6Fh1M1BbdCd3Q+Z05EQx26cp/wCtHgsNmpVGqxNfXJjkgALd2jDQoiH6YrE6TQW/S7EwIv8MpjaHkKoUhNiu1XVPZhcw/CH0sB1XfJhO62EHqsrQQWtnacI0DrhyOK5tL7/d8iQbc6YyceRc+hJVUWiqr0YJ+mn65A+MDG6hQMoj/tT7Ach0B6i3uUyrqWYifcJhDV1TCARbOuvZGdLQMREqkl3BEfCjAdmBEHcArnAtlqKXEFGRUBAEg+4hzgrwfeN2mlt2mRsuOJw2oJEUWWdo0596bM2JpBsqqDDZkg8cGML808yYmKef2IijxI8yJIqrrh6Ly2nhq9tW4gjUcTTRw2HqnngS0W4n8/XXjike/2H5P2U4tVqt/Pzzzzz77LP4fD4yMzM5++yzuffeX6+Z/7dF13T2boVMSyrzXHvJ5CmEhDg2WE5lS2Up2wbmMpUmPFWllCXC5vwgjbaDVIcb0X1ufhLms7Z1DJ/nDcIuiXyteNDGTiJ9sjkY1wfLObQsTHraWFzRKVyXNYWX3+1SzPZ4t1B/qJwcTw5n5S6gqmYbgqqxXqnljhEjGDd85mFXbNa7evNeLjng4uwzs5g7ufegtDd2VPD3j3bwzpmDmJXRZRl4bUUBf9e9gISohdClCxlY/pjZHmh8fPInSN0C9e5acReLShbx/UlmmU2PDyPKb1A2LB5RMxA1HbExTFRRgJPf+rjf9lY3bWXLli3ERLdiD/g4/+xJRL1ehyyO5TftYwnrBvtDGouyDcL5duRyL39JC1IRVtngk9ns7wpw+9TxDXd6r0M49X2SP5zB5PFXMXjyAs7yhpBFgbc/3sWgpZNpWZDHyOM0wgW1TPnd1aRP62qvpcsGIGuDOe6EnkRZHXicv59v+sbn39c3aV7hbR+i+J14Ym2ds1DAJnHtjeM685g88eAFqLrKn+6/lPJrrsUv70akkbFPv8oPI2cAcGDB+UjSDrI+/wVREJF7MSMXPbGSIl+Ib/805Yh9S/bUcMt7pkl9SvR6RrY1ct8ZR2ZHXbn1MZSWv5Ka8hbDcg7vX6Y4yz/irbUhPn/47F73D7nzM4KSg4v9XzElqR7PNV8dUWbKyyOYt72KFH0reTUGNy18/Igyb/3pDgByGqq4OymG63Qnhihy4j/eYdr6m9iX6WX0oU+YGJ1Izrx3GBhaQ3Pk6WiGwG5vLQtOnkvLznKi5qnEjEyh8q0lGEImjtOdTB63qMf5mr3Xojd8RNpNi3u9L4ADy0x3cYcB4oxzRjMupyfqbMnHGzi03MdVN1+KtZdYA4Bd76/hpF1ech+b0Ot+gPYPv6Jtl430R8/vGbSthOCVadB4iEJ7BgOCFdTazPiTlu2fQB/KR/m+jQif/JYMw7R2RRHFmuzrqWz4kLe23M282BhunnMJ8qw7ej2+qXAbNe99xW9PHEfeHNNa997jrxEWVK64y7RgeQvzqNj0Hcq8bHLnmbFSp3yzne1RGhZD5YtB6Wxo2sy72/7MjdMeZ1RstkkmqOvokczZuqHz0bYH2NhYzNC8DzB0FQwdXddQwgqa6kDS2yje9wKi3kLhgQJ215ezTn6PrLwTeeaWbvf/K2z5hq5Tfc89BHbsIOvtt7DlHenKOSb/XvlfKx+//PJL5+/MzMwj2E3/v0lCRUUUnbKAOd22CSc144gOMir2IPe6HiILlWtIgmHwXMLXROe6+PbsBzhn7TesDqaDILGlPcCq5nZOSIjG74nDEtXl5+wYTzpWTIIgkGSRcFs9jE07nrL2MvY07GFTzSY2HvYW9Rf0p2qmGbg/v33nNXT7/acvdvJmbJejWlSrsXt302p0uTU27t3DlNFdE3TOtmgW1bzEyje/YsiJEwlEWamcls2Zz3dFkG97/HGEt97mr6s2ss0XQqfD2WLGD9SEFQbUVTK6shAPEMzIxpM6ks8//wcZ1Tozks/BKbtp0w2KQwZDDsL9m79EVKqo3JzOuiFB2m0aF+6LIbU5gFWwMv64UZyGn+Y3fZwlXsf5PhPPHx9lrjRPGZ+BeMCPYXWAGHEvHOZ11MISNmNQn22XNNiBpvSfL8YqWRGtQW6878g8Kh2iG3pnTpXMf77C1k9fxnHfc7Tu2YmWPwHJZkfSQLRIvSaD6xDFMJD7QBbNH55CLG3cTjKz9kyhan52r+VEKRJEKfYdwHi0CJ7kUB2lzmx2WvKZ/+e1vZZ5yXErgdzHCMSLhGfEsPiLyR2VR8QgcZ4XuISShDTub20hGpU/v/UCE/btwpAN1j6pkZNdZZJ2tabR3DCUlYFhKFIYjyFx5YEMWg6UA6A3wMH3niOu8mS04fUkjjnziGvSW3wIgFpViJSS2yvkMsd7LwO23sIfT04hNzHlCMUDuiWo6y8RYLe8NX0WqT2IwLAj0WKvzoLGQyBaGJAxBAoq0CTTTTi/8CMwXu5xTNOqRWx/82lmZm6iUYxlYd4dFKntJA+dgccdzUNbvgXg7RgLs0SFvmjPlIBJfWB1mNE0H/6yk7pgK25sVG4vJn1MLmGfmcFPdnVNJ1vdABLvZ2czJNHGz40iPlFkfNIoBsf0DtX+xZWC0lBKkzsBmyRhE2VsooxbkjCaa6medxVpusCK4fBQ85k0eQSi7RZsdQe466U9PPGHLmJLo//uSt2TT9G2aDHp/3gWZ7cYxmPyn5NjuV26Sc0DZuf1JQ8mZUYu7Z8tRh98AR96pnDJoas527aHi0ZNhQjK+KaGM/hzhkkQttknkyxWcHFGHk9Xaly2qxi3LHGOAUG1l8mq2ygkCQJDPYn8depfexSp9lWzoWoDP+3/gZVN62ipLyIcGo/VdmTEuBpBsMj9JEfqUF46EASqorHQpdIRzWkJ7kYKVhBVV4+ojCfsS0ZK+Z4JI3r61EcJZhR/XJEV/6OrSawLkfjTQerOykB35yE4PIhyOgLwoVfFQCIJDREzHkEQoM4TR7Tfiy8lg+GjRpEQ9HJg1w6sxLEzZjP7g09wi6eIZCtECw8g6yr5xWtoSEgm81Alk9NOZvQ/ngag/A/34d+8irxZGTT/bN7jl/oMhqtJdGfj6Iyi1/XOScbQD5sODPqPGhSEfgMPAQLtR8ab9F5X109ruWkmdtz/Agfvf4Gy6QNIqq9AyBrSx8Gm/NDcxW/x9DtfUl9TGSE0M90GEy0KPuqoUXPJHZbYax2S1VRKBKEf9IRwhJ7WQ5Y8dRWD/7KEkpQ5fWZ1dY4bTFO9TqA5DqvQbQLvqFdUsNPAGcqnNHmnoQGTvvvKVDwwqH5OoYMG7tBXT6CFY0kEzgY+jfLhslV3hRQBcn0cQrSIJvuR9iRS8uSnpF09B3tcVxBw+K0VCBNBfvU4fO6Tcd2+8Ijr1hrNVAGnpccSlRx9xH7oUj765Yv4NdF1QS+dcPsNr8CWd0ANQVMhSFa4+hfY/iEU/Ezald9TqWi0NZUztIPC/uA2Ck433ROpwB2xuSwb7sQwPgEJONhl+bk8+0beKn0ewxHT5+Uo/kheGdHJ+i9XcHCHiczKUeNo/ngb6WNyUSLKh8V1pMVn4AczcOlV3A3kliSy7ccLKJCdJs2zroOmgTuKec9/QqXqxGs4mbfzSIbcrMoK3tEFWs5TGfuNE0lJojJOxB0wz9lctetXNK4pTe++S9Nbb5H85z/jmT//Vx93TP5v5Zjy0U0yXniegxMmkjIqi6QLz6f9s8WIiQOZP30qHIIZli1csSaDp4ItDPSMBeCebTO4R3mfYMYIjrNV8vucIXzTXEBQ62ZN6D7LdIsN6JC+xqRUVypnDjqThg27WMk6Vr27kJ0vf86tH31zBOxN0zssH32r/J3niRT57vtC/NFmPdG1D2ENmRTOhh00O0ihOUgIPdJXAxg5DrRqjcw/TmX7wi9I+tnc3rjPDdQB9WhuM7AzKFs5y6rx3KypPerIXbSWmoRk1mfnItRVcPk9t9GBhVq8QOVWd5fP9pLkWwBomfFHho49jZKzzyE22BUYiSiCrmOZdxmnbV3JulYfDZqOZu+pBAiRSPpIuELkZg5vfQHjCFxRt71HmYQBRElB146SIfMwzoeh197J/vQ0Sr7/BLmuGb2iipJYhY3p7Xz8bDdLgnBYHRF54u/P4G9vxQb4nSkIgoAoisRZHVS3V/KJ1cOTyUcGO5tVRhSxfrPa9pTblzzF15sUUlzJ/OWUiczPH4EFjbjU3q0rALIrAPUwcPitDBlyQa9lPn9pPmdlfspJv3kEwzB476P3aHbaSD79HOAtACoLklBDTgQBsgcFKD3k4L6kBKZcORtnnBvNF6b6oQ1Y4t2MPONhdF2jYccatM9iqf7nGlKumIwjqRcCOH/TkduA9hZzMvzkkW2EDRsn3ziYAcN70gF06Kt9WT42FNah7a8nlgQO7ahl0Oje84oYyaMQ2iKVLTJTzWNxgM0Ds++B5OFmllkAUSY9OYf0ZPPNUYr2dCoeHVI2fh7DLE4mpY9gYtoIDAz215ejC2FmJ8XyVinYpL4ta+GA+Z59/f166kMtAKRrcUxSB9HmNF2eqt9UlqzdlI+Dk4dzoKad2OWtnUi16XVhdmpBBKuGEWEzzj7QAtQTam+lTUwDQeadgSEU3SCs6zSEQjy/71vSylcC4J+lU7A9Ga/DirsbSGfCadd1/u6Pa6btxyXUPvoYcVf8nrhLL+mz3DH598v/OLfLv0v+22iXjROm4m5v7kSNpM1twpkWxqLqfKFN5/uWBYwJfsXV6Zt53vg9XiGKXbG7OBhzkObkv6LZBvao7/cfPUNcayMhmzmg2HRAERl5+QH8smnOvrfSdAtEa9FYBAsWLFhECxbBglWwItQ0MnX3PHRLDLKQij3KgstShbVtL1bMALeFcWNYqw/AESWTkWmuznoEswkCpZVtBFvDPHP1BM7KS8LbFmLE2q2MCRzksoIPaJf2YiBQLYt8EO3hpiELeG7/9ygt44ix20mPdSMJMqNrXVxWMYs9OU5ESUTCIGPdSoTynYhRyYT3fdV53jkvfUgGbQxwes2EcZiJ46b941UA3jzvJtIbGvnHMw9Sm5DAVyecTFVSHJ/UmgNvKOjGYmmncvsAVHsuhg6hPXsR7HbsQ0yrQGDnTgSLC885d/C4P4qvI106xxHgtJSWzmvR/XYurM0mFNWGy9GMWp/Nbv+HVLYWY88wrTsJU7/DUDxYpZxICwoRG64ZNNu8uIT61ijy8lJ6JA7r+C0IsNw/j13ZA0jMdJsBuBGnRUfcoAiUllQT21rKwIHFkWclmBBmOqjlBSoONWBT3BSGsw97nkbn34LcTq2zgjhHCbqgI1okoqJcJnoInTalHi0g42wdRkNaI7LQoRR1oDkE1GAjWYFSZjdm47T0zt9T3iCwOTiYpNwURAG+bTIZckU0sm3NjIwK8V1jGhcJfs6Ki44ESgpIu38hFCpHkyAUrqYl5KJ8ZgKehOTO6+j+7W2tBEEF/1DqBAu7rS5GaM2c0r6ERHsVDkVlefBmwq3D8Kky2ckOymoDjHCIDEozLYKGbqA3h2izBwlHm3T9CAL2NhWXz8G+pKUIeUXIskxcwzZGlRThw83eYdMxRKGni0kQsJTtZ0xrAU/7HsHWPoy09BbSkiLPWxQRRJFN+0PobXFUnvizmT5AMBE1oiAiiiL7C6q4qmEWA5V0mp3txIwL9VAeOxwy8q4gQptE6uhvYL/JlvzGgMuJtjkYGihnqOCjrKaOHP9uNqdfim6NQsTA+vNuLJuKejyzReME/FdOQpZkrIKMRZKRBBEQafBq7G/2siuwibebJjMk+0RUnxXZpZtIH1GgTpT4oeoAddWm62WQmkreaacgKmFkQ4coF6Isoq+vJbmwDe1EO+4kJ6LFgiHJKJKTxpeu5UBwNqOMLwgvryX5g++JHpZjXqAo8O2fLyb1591M3LybuYsfpKZhGYtPf5cFXy5AlFzomqn8DEg4jQlb28g+bjLehnICS6oQrYNYl/kxqc4xPHPPi533/fWtD5CwYjHTtq7r0R7+zZsp+/0VuOfNI+2pJ4+xmv4b5N+e2+X/l+XtMWeQUFvO4HQ3asMBRoxRyU1z0uAVaWYMxbutzJvdjm2XhlcwV5Ijm0dyMOYgE93pWFzuHvWtOi6J9Oo6pqYMBwNkvY1YaSet0ZPQMSeCDHkLXjWK0e4xhLQQYT1MSA+h6AooGhc3nUm5o4uyOhyAcGAAYkDBEjDNqP5kHULgD2mUVvVMwd2hXoZ1HSPWynVFFTxQXceEaBfzoit4ff1NABToaUSLfhJp4cS6p2h3FZNkkai21dGGRrAdDDQMUjlJHkNKqcmuKRmgJh2HJ2kcur8RpXg56CrlrgQktZEaUaTG60A3dBy6jtPQmSTJYBgoFgu3f/g6QcnCU1f8gc05Q3n8YFfWS4vcTqDeirdYAeOAyfoJGOEwgV0RU6tkQYwbgNpoZ6iksUbUaJOgMiDzRWnXZGo3BKYRIstvoPuj8Kp11LfWoKgabcUmlFNOiSYqJUxQKwTBQBCMyLxofg+xBghZZBqqazAM4bC8Lebfm6Y62JVrIzYUxhA6sCOYqz1M95c3P464Fi/1rR93x5Z0olAMDKaFTM6EfEsTRi9RF7oBLoIk6ApbHH5c6NhlC2ElZKoWgkC5WAcucMvttBs+3PqwyETXcTYIyuXsiFYYURUgwaf3Gt0R1awwIbSFXaGT0RGYYC8jiTLcQjsV5NPgtzIKiRlGIvbIStgwQNrwNVZDpz01lfiGBpIVhdKcbJql7q7IblZAPY5wUCAQDiMQZhQ+/up/Bk13EWifyqfNf2CUQwIbbFY12huCxNlE4u0SuleJ1KFTLNbhVhxILbIJ5zQMFANqpAa2t9rIai8mOqaRD9UwqZKIBT+DDpjpE4RuSoEQaaWDFgutzlriA+mUthps1qwMqgtiIGAgoWOnzlXK4tbFkTsyOr8NDPQYnRtjVnN53Rmc0zwXY003Pgmh43mAakThFDd3Kh4Avyn9LHIegWbgg8ApXC2XkVfxJRoSCAINm7o4cjvSU64YLdJStRnVAMUwc7HokcFAMyQQdAzNwcGG00iuPTKOZfKJbo6zeZmIqXzEG1FkflnSS+8A1TD4/uN2oGvskQhzbcpyhjqXU7QsBUMVqTn/NGq6HZcP7MmCK94xY8oMOY3JG4uJh07FA6Cq6Vu+zQGhaQVe4CrP00iGhD64kWcufqDHtQi9rKdDhYWUX38DjjFjSH3s0WOKx/8Dckz56CaqplOWFE9zchRBRwAlcQLykNGMm3kKcZgvysWPJfCFdSDTQ//gguYMFGsLgmbnkflXcPrUI5lZR+3dQdLA6dw4z6Re1yNBZ1IkdkAQBJ7fN52xnrE8f87zRxxf9voWRMMPVpXycNdLFWW04HDGct47ZuDYoA1bON8v8XNaFCMGDzyiHoC/F1XxZGkdSVaZJkXj2/pWoCu4sn7ESWS6RsGmW0jQncSGs1l60XbGP/Ah8weH+dsFv+u3/QzDQNUNFO1U/vrjIj5dI3JozgycFhtrlu/ikZ+e5HRR4/y4xWy5IobkmhB3bz0TbS6UpzsYXlVMQ1QM24UKLovUKcogJcPak87nRHkWrYKfT2zr+N0JJ5AzbdoR13AtcGXJXuS3p+Af/iec597d5/WmAe6/PY0l3ETS/fv6vbcOqdwzjeNj6knup/yaxZ/gUYr5eEHvyBCAc3/YgdWRywfnLOmzzKuPvIDb4eLC2y7vs8y9L95LTNjDpit/6nX/1tVPcFnhe7Tb2rl7+itcMuDINlu0/hPuOvAQJ1/1AKMHTOq1ni33zmNNgcF7f7mu1/0Alff8hGdEHe5Lzu/ctm+hafHLPfdKgsPS8F57Hb856zdkzp7dZz1Ldu5h7RefguDgjLZmmvVr8ekmyuiEboupBTEihqCjDq5Eb4VwNHRYqlaWHGLKsDHMPb9n0G/x/v34Fu4gN+MBJs6Zy5LPrmGuZS27Lus7ZuD7X+7jntKv2HjebWzZ/DX+bQv5IG4B27Oi2Zs6iAOZsPHHB3lQKGfJ+b+Q4DiSBVU3dB5deR0fCV9x6x0PIvTBJlux/DJ26Ks4/vhWU3vTFP686EO+iBrTWebu0oVcXHsHB5vN9/yfF8Rw4v3mc9U0nUtfeZMNFYk8PmoNDn0VomjHKiQyKO5MbllhxR0lsLlSw6eYlqKYmYOw1YUJ7W8m+vRcoo5LwNA05mwuYXn2YHZmDGBRbiZJLieaLKBrBppuoGkGF24vJNqnEdOq8vwoGV3T0RWF79/6kJjEJNYM/w5N1SmsXoXDuYU5J0SYkiNJDb/aVcDHKQEy1VgONuksmBhPVryXKsfvSTJKsAsmp5A30M6eai+lrfHg2cRrk29DMOysO3dVn8+tQ5S6OsqvuhpLUhIZLzyPeIzN9P8JOaZ8dJM9+/Yz3hLhSlQAEQpXrOWb1n0sOOUmhIjJOtlVzwMnPETD3gU07D6T9kSR8ncP8cjmGq7+/SgSo3pnydvZXMmpWw8RFmNADyMYIayGDz31BtLDJb0e45yQTLCgmOOcMmMdBvv0NhT8lLTFIamNXQUNnVF7t/JlocC2okPk5g9hcm4OcjcftCeCY8+wWzlJOcjk/e+w2z2HVfaPyA3+SMZ+gaB8iLB6BoJuQ6tupfS7jzlFtSEHjk4DKQgCFknAIokoijm43vjF51glCYeuMq3Yx7L40/EdaoUI71T8kP38qN+Kf1MU18a+y3Er43gzL8wr3jPJt5bjDYq0iHGkiyZjgNswLRmbv3iZlJ8uRHVORbBYQZIxBBvoGqK/3OzYwtG7tyGIJnfGrxVB7HVl1aNOel99HVGmn/2+zbUYio5h+xVe0X4qOm76XVD4HuOSJ/SqeADUV5QCoPTBdFn11WPYA1VMTBDhzZNMvpYTHoCM3iCjvV9vw3MPQY7pJqt++jn27ayiXXKwq25H501YBRejjpvEmsZibMCcoSvRvTnU14/F2dz7/anuBiz7I0p/NYSjzXW1LuhotiO5HjrmfCMSpJFl6T3ZXo876ggmRcCz4z2GrN5P5s7Szv2FQDzwpATWG3qf2ERBRBYFLAJ9Kh4Agi0agl0LE2QrL518ES+G2vEJVryahsMdz6is5zjov4bHVw/nmoUtrExeS0XDPgL1f+OKoXDFUNheN5wxSXWEgtFgL+NQ+xa2NjwHDYedszlEaH8LAK3fFKPWB4k9YyAfzRrOi6sKeAgvQUMkOaXLqruh2cstB8oodYngEhESRZIndyWIVF59nOzsGCada8LG9Yp97PFaSb69pyK9++nVuJr8nDtQ4S+L4MHx04h2xQALOFBZyNeb17C6SGFnbVfCw5MSxhOwN/CXmVfjsvbuJuwQzeul/JprMTSNzFf/ifRfcOUfk97lmPLRTXZu20JGRgZnnX8x0Q4LDz/8MLoms3VLO1u3mMRHccJFzCqrZdRlCynwLWXJbrhsvsHitgyUHyr454PrGXVpPqePNAPa/LZhbFDyGbRsKT7DAYbEaVHlWEUbXl2iOgx7grkgxfR6TQmjMzi4aQWr1zhQRBkEEV2MBlEk2qF0lnM31XPiyq/RBYE6w6AO+DE9F/eQEfiKDiKIEkFF4cJwiLL0PD4dMYX3Bv+RTUtM06YinInVCGGG1kkYWLE2pGI0GlytW9jW2GUC/eX71dRUN5qLl86Jz/SrZ6VEM33BTPaWWYEwS7dFYybeFpjvyCBZVamwp5EcqsNiqLxqXERi3VDC3i9Zz0SahHz+ujCO2NaNnec7mOxnT8oXFMseGpPiwRrHQNch7LSitf1oBpgJIEpdE58akpEyhx71mRscXZnoIUL/ydPAXNT9irx6/UrzF4dAMjDC/cN6uyef60881t6DTaFLXZDl3vkp0rY/SpobcANlJoy16J/30Jr5e7M9BNM50RZKYqgi0N3xOHT/PoIHiyk+/RQoMfN7uA/u42DsMspycgCRBGcGqcmpFFeWsHnrUmyAx9WMEr+f5oT9NOcsRlBtTJu1GpvtSCRRuK2Fpl1biBk2AnvsDDQtgPbQLqRe5plOlFMHNLbDFabrfeYuIdCl+Yy4/FMOvNgVPC25JNLvvprdy1fgWb4Xi9g3UZWuq53n60tUzHfaX7UC8TDlWQKigRa/6SL83azfIDmr+NuSdg7tu7SzXG1gAMmOQkYn7iGw92o2NwSIlw2uvP46Jq3azYZAhGbeMIhVWqjaVsAIuQtuqnu7Us7PzUvgoYNeLq+sJq6xEc0wHa91IRW/rhMrSwxV6ynpRmVvKCGCmoTd1dXnlGAQWTpyUeZXNNoxKChWSVOtOCNIvse+/pJX1lmRRQ+jkhu5bko7SdFuzhg3hTj3gn7bsOs6FCpvuhmlvJzsDz7Aktp3lulj8p+XY8pHREpKSiguLubEE08k3m1CDk8+eTgrVmwhOtpDc3M7waCNJiOONVVWRgsCKUPT4PsaworM5QvyOTQymS9f3UXxy/tYeE6QC+bm4o29CMHQSBNKcUoa9wyZyKzkGT3OPXjxOmKsfWvkUSMGMOWpy7E/+wy5J52EYRgYuoEomYPldw9egW93OQhWTv3tlcRPmcnajRvZ9s1nsPwHPLpGc/YgJFcUDmDqll+YuuUXijIH4TzpZPw/O0g/2451/Jxez7/uzyvwt1v49I2vafOGeKjaRV9dx7avkb2zfEzKSeFgTRlr75nL9wc288iXzSxJisDaYs4AYKpwiHyxhYakNYxyyyQHNzLmp6+OqHNgbTMFKXH41TbWpxRTkuFgrWplQVsKN994oKugpsBDpslbfrTxV3Xuf9XyYSDC0cprClj6TqBl1tO7wcJb60esajcDOiQQbP2jZn5tvHi1r7rPfdHJyVAEDlf/q0I/FnTAqsvsbZtP9bZojG53oRgijrZEDgf02vNzyXrvM9qWrATDQJBlxjKUSU0Gg57oIjXTNI2X73wdVUnGUuMhkLUfZ6KZP8iQQ/xuzeucmH4cvxs8r0f9Vk8MKdO6ctbougaIvSJPlFAkB0s3ynLz745IiS6Z+cRyZFHA2j4YPXMbgeVfEq5rQrIY2LNiyPqui5nYX1mBfeVerGLfJv02bwHiUfpOlbIdgPUHrui3HIAo2bl67kyKGpawrW4UY5N2EpV4B3OGX8PPr41BTA6yvb6GkGSnVpPYfO8zPHnttSz5x2soahuK0oyittIqyJBjKh8GBrHnd8G7DavZJg26jjcYMoOnBZAEGON2sHj8YO5d+hmNepcFwttQCwj8/OMm1iw9CVGAsCYQ3UvelLJaP9NCFpLXuzlH0LBEFOCDtfXE2j2svHsBbof7iON+jVTfex++TZvIeu017IPz/0d1HJN/nxxTPoDm5mZee+81zhZWcNyiv1O23mSLTDUMLrBCe7vO0pjZtJKEraaS/PBe9rx+FhQ1A39hyaftJH/5PgYw0JCo1pNp/KSYTxY+Axf+HkMAVzgDAXhiWyVPGnuJjdE60Q9BSxq26mWUvPIchmQD2QaSDSx2sLoI1PoRgIOr11Hc3I4odkTRC5T8/CrjfimhLN+JdKpOcdt3hPYWkRMFuRd1o8LvHIcT2X9Qob2kgJFNO7ANuBr/zw00f1NO0nGTeg3EkhWFKg3+cUimo8t8OMtDoryXqNTheHLGgWHwyecreWC/lZ3b9/LeetPk/eznyxifn80L56YxKjuRP3+4ilVmglbWGoNI8G3iBGs2p7meAhfsixAyP3vR5azNfo/YdoP4oBX/4IFUNS3FFTWC0bHDaaxcxJcuC+Wf7uCzLRVcPDqdtBVNwJdcn3IWPBgP+SdDfDfmwgHzIG8mDc1VlB5YAYLIkNBBvJqVz5Yv78znIYpiJ+JEiLS1ACAKDAiGSKOemnWfIojdUCyY1PKCYfC9ywwO/n7FOhA76utARpj1bZdUxtS3U7BoDYWSRFNsIuovtYRLgoSEIMMSqwjho8XvY8uWLeYjFASCwSAWi6UTStvmbUMRFV5d+RxirBNFU1B1FUVXzI9mrqRL6/ey9NsbiXG4QZQwBBFDlEAQaT+0maFamEMff4TP9YtpxBJN5I0hwGW5WZy++0bS2rtiiUI5YRLHDoykQzE7V+vnpfhLRPzffHtEvxOA6NHp0FYNMWm0/+LFItioWvQ5hiChCzIIErMti1nhvxGLoxpHfHGPfriNCdRWVjC5+i38GAhWAUM3GTINXQfD/K2oppVu/foiDF5DEmVk2YIkSWxdsRFVjGVF4X4ak1I51KqjSbF8tetrrLIVSZCwiBYkQaKsqcMNNQBHOIn197+BVQNBTiDt4mso2VdsvouSyK6KQo6zRVPdUAcIiBHEiNCBXhJEQgENURNpqttlul4ECRARBTOHiSAI2KKG42+tY2D05Uiije6opI7eVtC8EMWop9Vbjl1VuG/BMCoqxlFRuRNv/VOsW/8RUlyI2kA2qhBN7pjPeL5Z4OscEDb/wGXtJnoqP20Sg+ZMJ2/uJPY+9h0JaireSUpn9muAzChTqXjWFcMFE3N6PI8OBa5N1fHoXUn77HFJZGQlE++Rcbus6LpGW8F+gsII3rx+OQYQ57FitYqc6TcVEm9UI6I/mgkPfIABtIUTGZ7U+D9WPOL8LbR+/TVpTz6Ja3LvcUzH5L8rx6C2wJS3b+Syb39m2l4YdGIdLUlZEXeCOXKmhgr5xTqRb6NOZ1TTNmaxnprEbHw+K1VlpyKE3EiY5nHBgIDgQDV00pu+4O3TL8KweCiP0pAsEooaRtEgLs5vIiEMAVXzcUPtO8wrKEAyVCRDQTJUZFSsKGghgYJvk9HVvn3F390Kxw0K97m/L5k8/FsCr28i2J5H9LAy3L+9+IgyZbd9hU+txz8/kx9XrcQqhxkxbgmWGB9CGIZ7HiZuxEls21PJeV93+cKTHPW0K1EE1J7kVemOZkan7qWwIocJQjWyYPBn43ksgkpF8Ca+bpnDlrRyBh5ciEUR+WliHdUJQURLKjsuMgM0X/n6EhY2bafkgEnRbTXg5lYH1bLGw4PvhsZCjhCbh42nvEHed1eRoLR0bi5oj+PriuFHlu9FZiQWMzGhot8yKbNW/Kq6Ru3dxIkrv+bJax/u3Obyh3is4nViBy5j9apL+zm6S0qjStmcuLnfMrGtFs4PtnC9v7HPMs8WTUQL9R6vZHGdgmTtnfBMV6tRgxsx9FZGxc5niPvIwOte6xQKSLbd0mPbh8aZHBRye2yr8cTy1ZiZTGADl/IG8fTOxwFg6AKqamH9+vN73d8QFc3Xo6ejdHcx6SESKq46wp0WqLgIQ3MhuQqxx66i/eBfMfpZr0XpcF1b/2nuW2xV2GuOJDLrkOjcNnLnV/a5v7sYuoAg9j18NzensHfPHKZN/4hbyrvQML/7oYuLRTAMBEFCj1hkpif9hnTXoE6lURVVcixnAnDAlcdX8bP5Z8aFuKpNy4wuxWIIFlKFTJYe/JKI5tr1EU0l68Wy9wCItUs0B82x0iULDB+byHEXD+GGe5eR6hcJzjTZazFU5o8YxKwRPa3Ev0a+ueV+Bi3+mKQ7bif+yiv/5eOPyf9cjkFt/0V587GfO3+3lTpIiSnCuK8JIUKuteHp6cxu28ggfzmpf9mLKIrkAGO/XMaCzHYevvCMPmo+h1H3mNHYW6Uy7ANiMDKq2bC+gvvue6AzgHXVolwyDBvx9x06sgpdo7B4G/mW41lx4puMHnECmq6j6Tq6bqBqGn4jTL5vO5TdTFTOKwyP65pIOwaVThakSMKs1oNvcCjwIbJVIO7ak6h68iCte7NwtTQgxvSM1jd0nTKXg3Wb14PDijOmEUuMjxT/qdTK37E7eC9svBdEeGx6PM9vu4pKXxonZC/nmvkP0hqQKK9r4q5vi/DqFopG51MYPYKhUSVIB6uYP3U63xfkkVr9KZPsz2FjJ8P3aBCBIp+4MZm3TyllivuUzhiHjsiLxbfM4KRnVxEW4MmYADnxTrhxK/gaIJLGG6Dlnd8Q01bCxC/PBWBd3tkMOeNRdE3DFoJzJAlDp5MfQ9eJ5J8wMAy9E6V0z8adSHoLb40fZrq/OmC2CJ2/f7jyClrEaAa++y6GrqPreuTbrMvQNL5/+lGiAj5+88iLfLf7IPuiTWfFROUX4gYtQw97kOUwqmplxowZGIbBrl27aG1tRRAEzjvvPAzD4Id/PktmWTVpYirn/e1JLJIFq2jFJtmwSlaskpWZH89kaJmb2DYbpDUSvuhT9JQRZv4MXUX5+R08e5/lyj/ciZw32lzRGgZqMMCevSsYMXQmy998n4Qf3mHk6tW89N7beHdswhBFnM11WJUupdfjeZO0P39FR0K1rk4ErP0HrHsJxv0ept5EWMkmyA4EQ0EwNARdpfDNT8GA3918G9E2mX888QQh2QqCwOcTL0AQLuK1O9eAIXLF32ciSiKCYH7M3wLhoB+LdSQxlnsZPeViVDWEpoVQlBA37VyGXfXzVqYHjxjDy9v2sCgug3emvosoGKiGimZoqJqKNkFD1VVW7xBpK5ZpS5Sp8evE2UQuHeyOZGI285J8eTDMTy0aWWdD68ESfBW1CLKE0uLD4nGRMGUM1b8E8HjjmX7NeaaVxtAjhHZ659+Fm0oo/GEjx51yNVanhY5G7CJmNygvqKVuv53BJ9mx2UUMQ0XXVTNhHhqqWoleXczYfeuIy/mA3YGuYd6miowYMIpohx1dDdG27BfaMobxzqQx3PTDYjzNq5DmZSLFJINuYNVUqAdVsGIHzq9eTGX2OawVEggZDUzOOo2Koq/QtS0w6CTQgqCGUNqbaaiqQBIMElO6xhPDV4NdcKIKVgj52LpVZ9vORgaGJXxGmEkvfoIdFVkJkdRSw7Jb7mPutT2J044m1eNmsLZF4NErju66Oib/PTmmfAA+mx1XKIickkLMAJOZM1BTgL+2FEMJMGTqDbD4GtKD1YSBDq/uzINbMXw+fnm2GIvFgtXjIej3Ew4GcTqdhA2DAZhBj/GqnZ/KtuEsaUW0mebUDjFEESF1bO8XJ0rUCjbyRWgQBGKje9cmw7XV1AGGI56omKNH8KvOGAiAYWiI8clIwjo0I562DxYTc30X819LVSOKxYkudiEhPFHmyjN7zl0Mkv5K08GltJdupir0FYnuRpbeuoCde7+k3buaxNhostJi2OJtI3NaLNvkKLBKfJaXwI9F2xGAYSPGMnT4aDR1Po+++RLEK/zutqtBlHn71dcQy3eR7ziJNU1vcO7HzXx07l8I6wKaAR6lgc8vyePZ1XUMSbIzf1A03pYGomISwNU16P1sH8jUoJeyCTczesYVTLF3xWTEH7W1usS+v5wSPZa4AeP6LNNc58eBn6ysjD7LbPC1YbPaiB+YzfKB5kp0y6I1tHhM8jUMCY+njqamDFat6gknNAwDWZYZNGgQywwQfDIhi8bopNFHnEePKJ2CIZNscVEbHoRR6oPmss4y+zYKlPpf56yfn0OITQerk2/THCwr2cS6qBqof5rUWINR0wymOCxIS78mGvCPmw5NdQRsDqbe+id2Pf4nZHc8YlQfwa1p+SD4ICMfEpLoDaeQn7qIr8vs5MSa/dxhWJkuxfPS9BFYLeZwleSKwmKVsDl6tzJIFlNpNXQNWbYiy1bAzabaHSzRRrLAVcy8gSaHysr6Vhb5YVjOcBx9ZDUtK5YpVRv4ql4zeTV8sGGTj6GpHjJiHciSwK5QA4agkS0q/LTyix7HB+vghHPmIqRUU3VIZ+zc3/bePkB9wetU7d3D8Inn4IjqPX5k2/ovCTREUxSoQtBAM0T8PpUzp51JakwqAb+fb//5Apv3tJNXkcC1z73EiRW7GJA9FjmSJ6jo4Eae/P5u5AktLJDsbBk1laxXXgAKMNrSSbqryxqn3x+Flns1utRK+qF3+cecKTz64wl8XPsxr06/jc8DFTxavRTlvLewWEwLy97X7uXnku0AjLC0c6L7YYraphKyDcIjhhGA2lYbhqThjHOAJmM/tIn8+kKKx84ka5vJaNqi/uuGeV9KJisGT8cbDvLDoTWcPngGDkvvFr1j8t+TY8oHMH7HNvbXtPHuu99yevljHOcqx/naRJyHlfuaSQwrL2dQtjlZxAa8IMKK5maTQKq+HgwDSdPRZAlB17H6RDJdg2lpPohVDKGJFpKTFXooH5H4gr4kw26+OAMcfb9AkmgOuKp+dEgsEPE300nVHDPNoHE1eMuzsf60EucJZiBg9ctbcUlOXLW/cN+LDxDy+di85w8oClhkO1ZbHCmjziVl1Lnkhf6CGvRii0qmk4UzAitcWN3Edmc0uUEvuQpMzx7D5qBOC/Dsq934TQQRKRziw/tuBExFzxCcfHbuE9y0KJlf6t/h+PdLaGiIR4iJYuqLXXwbq0q8vLaxAYFDDLE2MC7Gh1U0sIoGvuZsAhaRS0+46de1Tx9iHBUkC760tF8HtT0M+TDu5GmsXTYDX3gDYa9Oesw2bIEAo2fdiGEY/Pjjj51lBw404y86vKY2RaKmvpyUxJ4uD80wn2+Sexj7fWexvwn4HMDfrZT5rI1gAa56U9F5xJoFER1idLObHfHtVMcLPAUosgXrnFO478qrepxrF0BM3/TqSB2Te9/uw/uKhxA2RH7ZdoDZYwcTJTloaiiirboeR5aJVhCOkl9HjCBOdL0nUujD0r3AUC7KyOnc1pnup5/6vthayTjMp/7m78bz1bYqftxTw7byFraVt3SWi9cEMoeZcVaJWTkE/T7aG+oZOGEKaYOHsuiV5RhG7wisNYtuwWssxjpEYXieiGzpu41CVjO+onB1YRcjmmHw9r7nyNSc1OzZAaEQAmCxWLHanQwe2BX38No7t/Ci9jNanABxIgkhpQc8K/b8ntT3rYhEFz1DbuSdDrbVkx2TjV6nU9pQSnRMNmqNwAdL7yQ/ZgASUFTclZiyuFRmumsnzrJCNmSfblp5NJ2gw7RCVqJx3JY3ySxdjz99ONGySVR2/+Tf8frlZ/XZDn2JYDYHv3n9fg6Vz2ShdjVPnv8HBo4/Fvvx/5IcUz4iMiTFw0N3XUzIfxYr/vkw4X1LaA47iE7PZcTMWZTuXMy+/bD7vjvwDz+Os886B58zCldOHn897zeoqkq4pQWLy4XF4aCxoABXUhLP3XcjcvHXWFSVMzYUM2DJD9iTe6ZvNpWPvgcbSyQIVO5nzhPoQEX0D83sOqCD8MBcGTtOPYvUCVW0vPoVTUtHUrPqR3TFgtuw05AYZOZjjwHgtNmQ5akoyiakw6Bzks2FFIHKdeRHEUWJt3fuY6fFQWrQx7qTp3eWz8uZQlJlHFHzMjsDKJsXFdDeXMSBqFFMOiOHdesr0etlk4ztlDt4Zk0ubxbcjz02mZBh8PaJls58KwYCim5QW9/ATwUK21pdhA2JsCFRp2YSawT5dVEU/TbcUUuoUf0jXfqTqXPf7vz91JWXYHE4mTzZTI+3KjoJLRhkZnx0l+LSbdL84IbriDt9Cpdf/OfObR2Wj1Y1gwkxpUy9qMvC1uBVWPRePZYIdwqXfIkxaBC+NZ9D8cOcIKdxx4xnScsayuWvX81ONvDsm2+gSXKnS7K7CELfeYpM6ejjfSM+rsyp56XiZH73cQF8XECWnMopUhlvvfUW115zLTEpcYhC//l1ung0ep7nI99QPLRzfHpXHEHH09QOTzDYTXISoqAe5g1NYnZ+InOHmNTwhhEh2zIM3nx2C3qBl9jUdG7/+Lte64nJ9dFWrbL463Eg6AiCbsZsCDqSPYCMGQMmWXVka98oJ3+sHytwxfVX4LQ6EASBl++8Cev+FmoAT85A5l78O1Y8fB+aEsav+NlY8AuJuFECPp5jKUgCJ7RkcihKx3DH8MqwbFacsIBZ1WU4Ro7ocb7POYU06hman4to95DlSSQvEsh9sO4gSpTZHn+vXQm1psXi7Ko03Fjwxwj4DAcbtqeR2hwmqWETPoedRmscDIRg8wvIzRrWZjMWyVm5B2clfJM7lct+Owe36/Al4K+Xq3J+4u6a4UwqaUUNmwqbrussX76c8ePHEx0d/T+u+5j87+WY8nGY2JxO5t76Nwz9YXYuXczKD96i7LNfyE+fxegxFvas/g771jW839iIHp+MXtfApu9WE/b7CEg+RJuMKEqIkohYUoySlELccB+50bmU5V1EWdk6KDNzDnRMIFbBIFi/m/Z1D4LFhSA7EaxRkY8bvbUZr1OiLtjAobZaJEHEIkhYJSkSnS8RimS1NbQwqqpE8owIEX94bxNmB8SwS1kx4pN4XqtjjFzI+PAAmm1+QsOc5J84tgefhB4ZqMPhegxDQRDkyEeKfIvokev5urqBexpDIEqcHNXTrB3TECZDjydjrunCaHjjG9wks93uQVJlJp0+m81VWwk3d/Es3DrtbBaV/EA1GxENgdlzes9KebiS8fv7nye9cD23vJuMfeNnJER7mLPgLMZOntA3v0MfcjT1w0BAMHSMcNgMuBPFbnwYpjTqClFK1996IIB4mBtB0zTUYLDz77uGDeBwUX1eZE802WfPpfCtL6lvqKTWW4VkGAiGTlgJIGoQ69YZMXcKYWe0ibiRBFRCyFotKm20O7wUfno3KUITsWGF1PQkct0eHHYXzXVlCIV7cKVqiCs+IwqQKstoPHQQSZYRLRZEUQLVIBBW8LZ1Pa8eWYMDASyGBUuwGfy1QEffFCMKg0isbMaPREkqXt2gXFA48Yz5fPbdJ7z9+utc9PtL8IltBHSd0urKzlxBRGJ1zJ86zYqIlUZ8vlqsVhcvlpr8JMe7egardnCU9GdJGZcTQ0k9PPqbkT36iiAIyJKADDiSHfgKvP3yhdhjRNqqQdQywBAjH4ktLelEtzgZmA4x6XG0BN7ql7ultK2UQeSQHJ2M1Wa+U3J7M4pF4LY3PscagbSuESUUJcyGguXctPGezuMtKrw27EHGTTmL37x5GqqhcmZyLDz/VK/n84mDUBLmkntRVxDv4JTBABQ3FXPOuHNg82PMT5/FHaOvQzUMPmh6AdZX4Gwx0ERIbQ7THD2Q7WNvJaF+C+vHT6G+xsc4FAQMlo4eydCSYgYEvDSoIt/lTeO68b8uCLwvOefkDZx+fAN2e5ebq7a2llUrV7Llh6+5+aHHsDn/58rNMfnfyTG0y9Gup6GeH/70GPXtpWiGimaYbo2CnCEE0weQ3VR71DryBmwkPf1Av2VG7m0jqaF3tEqLR2bLmJh/+doPF6MrhQRgGj/2vTcAPSghYBCQo/APMFc9Qke8YPcxMLIhNq6cESOX93MioTNM7vvN1/DRxIiCYOiRSnQEDN7ctw1b/tMIRjcdWNfRdANdlBFEnepd19B2aARvHO+hNkbqzEgiiJG20m0YgNwcImpjB5fFkQP3nMblDPQXERYspLS3MbnQxPsuu/oaTr74AvKSU/jm8afJfu9tVElCkyRUSY58S6iy+TssSmwfNZa/PP1on7e/ZfYcnDU1fe4H+GF0hyJhrnAFw0AwNDoYQAQMVFFi/8AR/DjnbHM/HcypBmbKGYPr3zR985Kgoxki2we2sD2/tce5zlyRRoyvb/KrDnny2oe5sCTM7QfMVWJg6zuoZWuOelx3+duES1iVPqbP/TIqS6x3kSf23j7vqfO4T/09AJbYNdhTvu213K+RS+NCjHOZSvA3nMXHghnLJCg6omEg6qDYzfaPD/qwdgRlH9Z/VFXFGQrApiYsYkfiP/PTQSWyIO9nxuatQG0fTSc89rCPv00h1JKOZ9D+CDufyObN49A0mdnLlpNcV4cvX6T5Iislu//WwdvXeUkm5Bb8dRKiLvHWnFcJKlUMqAwzc6sZ3+QfP72jMM5Nq4j1+Bk8UeXHpFoMIEZ0Ex+VjM3qBAT21R2gom4Iw8Q7scgmO7FFNj+SKODy6hQX/ohg15l9cj6iKCFJprJ58ca7GOkazE2P7UYIW1k70M2H851cMO1SNizbSGKZQchqIxyXwoydVlrik1Gs7QiG2OkualMO4dSaSBs8NBLAbbChMkCjNY6RaR62W3UqknNxW9wR62bk/RBM5S+xsY77H7yRyuHjCaRmgSRT2hbmF1s6s84+gVhxEanC88h6CsfZPibU6Kd45RY21XyDPGQYUVf+oaO5Is+z55MbFuVgaFT/CCaAiooK6uvrgS5X6OHf/UlvymZfCuivLdvf8YIgMGjQIOz2/hli/1U5hnb5PxRPQiLnv/QkbUvLaF9ejiXHTdS8dKypbkKI2AXTlHfowZ8IxAXJvWwamqaiqSq6qvLWA/dRY53FGb/50JyQI5ldoSuCfe4Tizl9WDt/+u0J6OE2DMWLEW7HCHsxwl783gPg+wzDPRtbwulohoZm6OiGjmpo6LpGc0slqb5X2dlyBnkpQ7qSh0VQGhgGdau+xRZqY8j0WaBr1BYcIOTvihGRwkGcRbsRoqeTNSYfp8NuojwiEf2GZn5rdUOxb8knbUwmkg101IgFRYsknlMpqyihsiFEXr6Dc4P7MRLckSRrQmdasw3525khqWSK12AYBqH9+5ATLaiCQKvqJpT4GVGxG2lnJPUxMoOCAjluc1XXEPAS0nxkROVyoLmBOofI9akKXSiLiJoSee/DNe1IhkizNZZUo2tyllb8wOcbl/H7F95ELy6iJTYO/9nngqYiqJGPoiJoKpKqEr9mFbN3bum3z/iTkrC2tBB/8smmf1uPPAdDJwKjYdyGDdTFp2Cfezr1u8vxag6GuktwJkR36odPRSVSnDWYS+0GumE6EToSjHW04ZCBAdR2g6xhk2ghzNhMG3KUzeTxEER0QWDbD2tJTPSQOfF0RElGFGWEyGf7l88Q1CzsHWJSpV9c3MXXIMVkUXPZYBAE3J/8jG1/KVH3/slE7qiq+a2p6JrZB0MvvcYosZXzpnco0UK3UAKBwoZSntk3gN2DxxGbmxfxlemRN8Fso7mqgMNfSjAqgbLWdD7qMqIwzzWZ+SkLCId1AoZgWhmFDi4N80SCYGYH/suBuzhUkc/cCWcQVvxMa2yhpPZn9qgjmDw4i6BmENR1drcHCLqtDJBFXILQ+a50iGFAuaJTlJDKTHcDNlE23wnzck2simHgtpuc5aLg6ux7nX0w8m2PrcKZtI+wOjDyJHU0zRyCk+tMXhzXQR3/l8l4k304nM6uxULHxGtAWPbS4Kwm5N+DIEKU1xzk/VFRKBWldFycFG3gGOxFiw0wSjZQZJBFH4JaBKqpzE7zKKwPNfPhjjoz+RwGKmZ2iWRV4LdeO6EYG2GpiW++2dGjn7vSXWwP7CXKr3PymaYSHFfShr85yPKpl8OYrrLji5toi1vZeS+ibkUXAMOGYiRQXtcQaRNItFlwiy14G9oZqQcIylb2Jw3sVBIiXQUMkFpNS1b6ns3UlZUg6Rphm4fNM6ezeWkBU9IFrhwOcruD1hWloOikWjMYFjOFVl8M1xwoP+L97S6johwsmTCYdV8V4msJMeuiwVgOc4m1trby+uuv91sP9FQG/l9Y85922mmMG9d34Py/W44pH79CBFkk+sQcrJlumr84RPPr+7EPicNzYg5yqunftyCiW2zEp/ZEmggGIDoi+Qr6OoGEIDmxe440qwPQths2f0Zewmjyck1Yr9YWIljYin1QDFKUlYOVeyk/8CoTh5zMtGEn9FrNo0tasR5YQ871d5KSGMszz94IFOOLFVA1hebRKWhNwxheNYqREwczbGR6r/UUflWAbX0q8eMn4IjtXXPe88UHzK7OIuUPU5AtvXezr7b8iNICg2bfZm6Y03P/T183E52zlPaKcajyXBodAtfFeJBEAUGMYUi8i/ykKB76sohvDTs33t47twPAN9f+TH2jzu1/f4qFr37Ij6l7iK/Yz4DUXHY2V3L/G2/wh1+WAjD0luv7rGf9RRcj1/Vv7TJkiXBcHGmP/q3PMrWzzyTKksj4Wy+juaiWD5/Ygycpjcn3XdhZ5oNl93I2X2BVTNcARILpoJOTwjGpiqadMezdtBmLqCNv1UlOjmbaQ1911nNRhDVTVsLdw5zNii57EASB6PZmbnrzId4adCFntyUgGhqNYhLTU2bBngABdwUBSsm8pO+ome0vvc7IAemcdGrvQYJbCjbzzL5aPGNuIHb41F7LAJzT7ffSD1+jTtGwC7AzvJFHJ/4dez9swB1y//57yMqZxPjxZlBszj3fA7Dilglkp3Thm+7fVMQr3jZenjKW9Kje+/Kra9bzlzA8f+PpJMf0HiewcdlB2tnD8ae+06fb5euvr8BmWcupC77p3DZjRhkrV53GvvxY8p9uRsnQ2TkynTZ1JxMG2pl24d1HxNd8//QX+GoMvhcEDAx2DmxjxiUPc/vgni/Q26suIijEMXP6e32206eLZpLmHsrWR3sm4NM1nU++OkjjT1XEBgYQlwZzLjgJXVfMxZWucm54FkHRS/mrd3Ued6nlJxLlGN7Mn4xHt7GrvIEHQlb8cg2WcDSKtRUBkdzMQRRW7UEGTh4ykokXXEBvcvejjzM92smiU3qfJMsrUvH+A5qf+DuzTjfv4d1Xv4Yi2POnWbg8C9jxxzFUpzjIeGgirYtLwCrQtqmBOF80a57+C0n3/pPWLwuI/8No5Aw3Ogbv7nmHTeFcinUHixf/yKEfQTQsNFf7OPePXTmNDMNg4cKFyLLMzTffjMtlzgcd1oX/qRg9FOAjFZW+lJdfU3bVqlWsXLmSIUN65+35T8kx5eNfEMeweOyDYvHvqKN9RQX1r+wg6YYxWBJNE2avkRW6BmL/FNlH76M9gwv1kErTJwcJFbTgnp1J9Ek5HPAFcQIP/LiP4i/N+AxDN5AkgQun5fDXmYPIHjyE6gNr2LX7AHFTxlBTUEoikBiM4vthuyh1VzK5NZlpURLC+0UUTvQx4Oy+aYn7u+yi1iKOIwsdjb662dG0/5HHXcfOXTtJGf8eMJcGyeCW5vquAvWQtEXnFMCi9Y/y6TDXJifFcfO9N/TY993jj5GzdRWbctMYUXFkMrKe16wfdVARNQ2jl4DMnhXpZiwIEJuXTIyxki2VyUzUNMTIsQtalqO4dNrjZne7j45+1hGzsxA5ScMTTkfRDPYXNFLcqrL30pNMa4kBXPkYiaF2Lol1o+sauqaZPDGa+XtFQxsHkjPxOdwMKiphnz3OrD8mn8Xv7uD41HQ0r6Ozox70BXmwsIp58R5ckkiUJHJSQrR5Rf20jRBBoRyes6Q/eXT6/fhCLcS5crjkpxv5aMffuHzCY0c9TqAnIuay4+J5Z2sj3286xB9O61I+OnKtVFdU8NrC98nIyMBut3PRRRcdoUR0cW30I73QtHeI11dOlLuna9XjyeLUBTtob6/Bdo6HbV/9k6a9TUzPlPi5IEzl07dzwnnXoO4vY9Xf/8rmnBgSWs32G3fihZwzeAHj47JIdsb00gYaBv2722TBjywdGSDtbQ/TVGMiokTA5XKSlNT7WKAun88bq4cRsyGVcaFdlJ77C9npJqrnd9vLIcqK1dCIacsgftIwdhasp7CqCw3zw/79HHrtR8QoOwOGpREVZUcURURJQjQ0lHBbPzcQ6UtaV+xaRUM7MWErLo8J14o2BDocstEn5QBgLW7CMALkfvoJDW+aOYeUolYcWR5A4K31rzG/cj6+4RNZv2cjJMP+2PkcP8BDfVkJ7955A9f+8z127N2HpXoTlyS34/7pdvjNq/2296+V7mPM/0aJOVxUVWXr1q2MGzeuU1H6b8kx5eNfFMEi4hqfgmNYPFUPridU0IIl0WkOdr30EdHQj6p8wL8Wvd/04X5CBS3mcUoESulx4AXciQ7yjGh03UCQRA7uruetHw5S6wuR4k7GBex85WF2vgJJgGQdjm6bwRT7Zu6YcR7WA1YSVpivamthz9iBzuvpuNZ+3onRiWPgQP8Q4u5ukd4kJXMshftPxat8wcFJw6lvD5mkTppOQNG5a2cpOz0i/qCIRTsKyscw+rze+6+/nn88p8CODWwfkMdxvRczRT861FZQNfSjKh8gdMs94hACtABr/vYFM+4zIYhxAT9WXwwTTuw7vmTx14txxmcw/+q3AZhZspsdC5+L0Lmbgc+2UIDTNC93T+qdLfKhZZs4gBmGoAVWYrF3tUCq2gKko3srOjvpT41t/Bz5dMiCxGhuNgwafAp9SWe3+RfG0olZZwKwr2Y1AIr+r+Th6epc9587iXe2/sCSPdXEu3dw9vThyLLc+SRX/fgDYPruAerr60lONlEcYoei1+/Zer+p1c3t/L2khvEeF1NSx6Kqpb2Wc7vNrK1lrc3oSBx/xV9JW/4p367YwnNvLWTy0lXUDP8bCc1Pdx5TFmxmQcaovq/I0DCOEkxtEYPI4pG8LC/ft5YoBRQBRE3Eau9biVEE85lUnHUt44ZcQjYQVjRa2kOkBUUGFe4mo7KcmpTJJB+o4PitpRQmpNAYF01dlIJDVjlUaQbhHzgsNM4GhCq28faqb3psz866gjnZ8zuVDrnIZDQu2LuWkoYK7EYm1aUH8Lc1Y0NgRHWI8M5tnS6p9Lp2WkULot1OwpUjUSrasWaaVO6GYTDCbsa+ebfXcZJzAvWpNcRvCrKl5iMaFu7CClz6zRJGFe3jfj6FWvhn9SkU6tt54pwx/bb5f1N2796N1+vtRND9N+WY8vE/FD1svnBtP5cSrvBiF1w01xSjqSrtJTUgCDjSYsHQaQ1qqJpuen47YPndJ14DDE3rO0Op0JGJ0zxn9Cm5BA+YznBrtmmC9sjgBUTX5zRry7BIDt6Y8wi7J2Zzx5ub+WGFOeilp5yOXQ8iGRon+kVkeRAIdv580/0AbNprsqyGoe859rCkXL2JLB69a9mCB7AeBWjib/OiW2Q8TgseZ88B8O6gwsU1Vax0xOJu6DtxGpioi74UodgoN6ecdyGrdmw4YoJpPbSa3dtvQQ5aEbEhas6uKMM+RNA0DLn/+zc0rZN0FuCk+0/hrft3EvD1VKKONk8LogbdAnbdOSOYfk/P1ZeweB261HfCs+zBuXCwglZ3LPEtDSTMbmLEA38lFJfAyK8WITotFJ7UBd+dH+/hoUjAbofYRBEBg7KW4OHVA3Dd6oMsqwkxLcZDs6+bSVnT0INBDBFkR98rsQMNJn386JQp5rM82jNA6OQ4AXP1aBF0trdY2b64gminhZMmDut8lNNPPo09a1cgCAKBQICEhIRux0autR9NWehUUHoqR+dsNyfFdS0+ZljcaFrP/Xv3vU1tTRuVldW0t+vU1jqw2czc0kPnnMvAcXPY8dMHPCaehzXFxnW7r0DXKnlo4NvUNZQCT/R5TenqNkJa37lRDMPAJgWxyT3L6LpOlAL+VBsXXj2Krx/YhMPdd/8JqCYBYQf03hdUKH1kAx7F4EMAsqmr+ZhWdzb29a/hDDaQUNR1/PWzb6E0JpVTYp3MnZKEKNHJCvzUj/vJEg+RL3a5xFJCGymuXW4qH4ZBoxtWVX7JM88uZHesj4D1fiaIhaS+9QcAKjChz3UfejvriEXC4TgITEO0StjyYjr3CYLAq5e+yskfb8RR7COjRcY1NJcyo4ZBRWY//Og3VzGm2owXWeU+g6npCo9uvwQ2V5KS/TNv7X2HH8/+kbSooxM+/qfEMAzWrl3LoEGDSEw8PP3jf16OoV3+F+LbUkuosIXg/ib0boGbYT2ItdvLstD6Oe8MMOMJMDrCqjpGNIEz99xIqjcXBA1RUhEkBVHSEGUVUdIRrS1kznoCNZAMWrQJ2zRMaKL5EUBuQLJX8WHLaA6IcbS2bsDmGIzdGk1YM/kIbAEvsW1+ElpG4QnHECME0VUXAacTq82cwGqjYlk0eBDjG1XkoI4WbQ4o3Yf69LJ9JNfvJ8eW2kc8h0GNv5F6Sy1b83aB2GU67IjYFxCI1qrIs4Y4XuzKbNpSEiDUoiHJIggm2kgNiNgdk+jQ3gzDDNrU0dlm01AlaIhLwZaaS0dEBICCgM9qxQCCWj3HSZs5Ud7V7W7Mb1VRCba1YgDaQRtCXa65VxBoS6kEqSveQq2Ix+9KhfzBffaLs799FndGEGvmYTlOur1ppc1+FrKAfekRX7th0N5kBnsm6ZVYRY0LTjXz1tjtGXREe6hKG5Lkor25HkmWkGzmMUpzrhncGkHMdFJ3GzrXJjyHKliQIjOt2IHFiATwBTrgsLqBJ2QgCvD+H6/E5/IQ8iSCKJJZuBMsTqJOuBMM8MoiIUlEMsCuGdhVg5phn1AdU0Wb09WzjwN3uh4nt0bhkhXtVAzcTpJUBQiEqwUCTidzly5lx9jR6Hl2BFFH03xkZO7B6TQVCGmvjzsTzevMDaabICFR7IxADKgBvFKAkMW0vCiawvTo6bx81sud17CnpJZ95fXc8X0pD5+QyiXHH8cdy/azcG81Fw5LJdnVk7emQ+nYWFjGSoeDV9oqSbDbQeiWKDDi26+ueRt3/hqSEh5Gkm1mf1c01jZ5WWRYOd8qkND+Fbp1M6rnh8gjV/jhh6/RNCs2mxerNUR0dDUD03dzqrUrjgLDJItbuTWbaMXgd0O/YVjhDwjY+cusl0zLqiiYiQJFAQQRXYD28jMwnJCXdzuiYEEQrUiiBUGwIog2whps2/Vn9vlvYM7os5GAeFnG0HUWP74NgPk3jmDJ87uZcG4zE48/u9f+XuWtZt/G6Wg5zzA/73RKy1uQXtxFu1umfXwMyUoI5fV3USq2gtdE3exLGUx6SyXuoI+a2/6KRZbQwmEMXWfsOScTm2S6xqY+/B5TclT+fsnlACwt+hpKbqPMfQmXT3iA3eWHOP+X32II5rNLDdhZUrmOuojl8UDWBXhSJ5AkRyEJYqcVuX3VM9Q6bXguf8tMQWEAQRG3aELRBUHglpIK7LrC67kZfPbDl4x8/wVclX5s58G74vmkGjU0hmMJ22zMrKtDydhC+5gwz7daOG+F6Rq8/pW5ne2ktoYQJAGpD+baf7cUFhby3nvvcdlll5Gbm/tvOccxtMt/SFzjknGNS0ZtDtK+sxrfItNkaxXttLlasA7woOzyY7NHM3VnHPF+gdTmOprmLiCYO7ATzxq7JQnN5WXsLA1N0QgHNXRFR1V1dFVH122E6mdgsVtNIifdhKt24B8MdNSAHW9NFhcOvozpk+Zw+o934wu3oBsGsmjgaqllesU4JEOiWfYTFq2EbCbGXUZDj7hv6iLQw1qnQIwsoxpHmrlDhukL9ukhbErX6lI1VGrCXTwKjpCH2kAthmDgsXq6UD4RfbdRlTgYsDI71lxFr2hv5dvoVnJ9Tk6tT0JAwF9vRQuD7qqLDPrQgUEUEMhp15F8JSQ31LAnLQ/BMHin6DqidPMaH869hheyLsKtulBEO/Nbt9MDQgCIsoHhsRGb2IDPqdL6Xahzr1jrIRzjQ5Y8aP4g9XGZKNHx2AJddPOHi3OoSpQ7iKo09FFCIDexjRythLXBLjeFZhNQwzqNFheiodAS9BBjb0NVW01khR7CMMLohoLVpQLd4lzEAAIi1jYfMYt9CBHgDwYoN5qD3agoJ5phoAGaYfJjaEBDSKFF04kO6sQiohkG3805jaGlpciamTFWTR2NMyY3QooFbjTcHQyiEiBDe+4ebMEMDLnbwBZ51hO1PWxLzGf76RsYdLCahPg4DAyKWs0ZftnxxwOQ7lAJKdDU5MHuCJOXqyGurCTj8xYumyKxZ2wKqZrJ7irH2dHbQwiGgKEatBqtHLAVoMo69VaF2kAty/ctJ94VT5w7jgHpCVS1loAYoC1ott3BgibkCj+fVvSSiLCbWPGyveIjohR/r/s92e2486Gu4d4e23OA6wBCoFshoNq44bOCbiXGmF8doSCNkFBxPCM+ub9HPQbQctUbKCIs+ioRZYsG+ODty/q8ZiHOTevD7RQV/b3X/Yomc9fKxwjrVv65cT0A53qt5KhdLsMlz+8GYNOnsWz67GcEKUTq7OcR46pRsaBixYEPF/Dyrmq+/+wp9rclcIBE3vCtZtjyiWgkIA05C2v2bHw/3o0ApDZX8uqwBdy57WPSnu55r+u/+Iz5iz9Hknu6LnfVboUSMzjdJmhUt1ewI1RNY/qLndbhJuDh0Ll85u5Y/K2C6p7pCQDIgrFhO0t2HP6Odv09rWAnQyuL6Gi90hmnde5rtTn5850vIEsSDzzwAKnLlgPw5Lgp3Dv1Qmr22Glr6LICtnxfhHeVmTDQmush6ZrRvTyRf6+sW7eOlJQUcnJy/uPn7k2OKR//ByLH2omdlUvMzBwq/7IWFJ1oPQGhAHRDRLeA4bSQf7CeCYcMBj50NfKAPDNVuyDw4ufLYHATM04/h80/lLDhpy6b5Hl/nkBiphv4Xb/XsKfwEL88WU70MAd22cKSBU/32H/fi/ehWBSuvuZqMuP7zjr6wa79bGkI8s74bIYlJfRa5q3VIUp/LuOiW68i1tmFgV/85qPUdKUMISAFMDC4Nuk2rj/58iPqeeKrF/io6S1OPN1EItzxzkgAitP8XHHXl0iSzOeP/pWS7Vu44c2X0XQNb1U9rcVVtJXXUFV4gNqKQuqADN3NQxefAZoCD3W11eh2M5jsOFcTtYqDk36zss97X/LlSVjsLVz60Zd9lnn24QdRNY07/vjHPstUPv41ftlB5u3mgETFZngnMnCljISEfNj2Hi1GFNPm53DN2ExSomz887X3WbQ/jh2SaQZ/ZONtnJL7E6fkVxAMVmEYpqIyccJ3rPx5AVZ3ENtuCcd+K05LDIQUlJJGLCUi+nFxCBa5M95ovK+J7+aM6fV6vyiu5w8llTyWn8EZAxIpLWxGH2DS28cnuoiJd7D6hR+JqbBhc1UhSBrRZ47BMmxkZx2GoXNg+b0keFI4cdaRQXeXArt3/0Rt3evEzHiUcePOAyDY0sKbf3sUnygwTBRZcM3fqKqq4tVXX2VA3oXMnz+fQx9djkoVsxJO4Y6bnqDu5cWES10YVQpChLK9wSrw92wvaaVrifK388vIpRxSDnHTxm50+hGjmHswjMz8CoCpmXHsLGrmpcvHk5fo6hGD1KEkf7OshFe2lnHO3U+TGu8woed6JDFcJFngmp+2sGHNCi665EJsdivhYIDGK64gnJ3F4LvvBF3j4e/28JM3iQ8uHRapHzStHZdLxzBUBEHilfe3stobS+6bT9HdciQIAnl6K5qRQN3O/SiAsPATM8BViySm0zTzb92g5elrcR8KkTX2C6yCgq4r6EbYVGB1BV0Pc6imiLBuJcrSTiDsRhNAHuAmPT8BTdWRWxUsPoXiHU0kDmgjJgsOLfdQLp5DcnwrGGHQQ7TrQVbUhsnf3YjX5mRoloOCIg2HZTWpwkvohp0ayyWUTN6GxytiWaMTG/JS74yl5YnnScnOpGrbbjImjKJs/TZynvwrPzz6HGOvOw9NF1CUVioq3qdx31MdtDgkt33E3k0foRvJIL7EPGcNU+NiwIDXGqbjCZfwZP7ZkWdoPqOWYDsuiwNZlHmk4GP2yRqPt+2mbchA1i7bR1LdQAbMiiXeE4NhGBQ0BrDK0Zx19kmdHCTt7XvRdIWRI07FEnGt3n///ShXX43gcPBmbKx5gV2pcQCwZnTF1YSL+wmg/TdJXV0dBQUFnHXW/4e9sw6To0rb/q+q2mV63C2TibsL8QDBncVddmFxZ1ncYVlY3AkaLASSECFEiBB3m9i4+0x7d8n3R/VYRsK7u9+77Pflvq5OpqtOnTpdcs5znvPc93PuvzWA9V/BcePj3whBEHCdlIVvWzWWfjEgCuRv3UOps4ZtKY2sz1XJjsolIf9Zdm3chYCA2WDmEp6AvbF8/ugGDEcFQXgbgxHjo2e0rCVLUucgigZ3A1KNhGugq0fDQ/8N+v89rsW1KJ0etWIXclUAsQCIliZqpCaWnLuENFfXlN2jcUfi7bxS/Q9GHHTRUFFPfHoiasTD8NJFZ3QqbzU6SYzLpm/WLKIskUh8yQgnPcHhhnkITaWcIdiolOdxlWVoaxbh7hD0uVG1YI9lNE07ZsSkoEeTtm04uATCPjBaoXQzlGwEoJw4vll0kNlLDtLL7KbAH8vadjTS/FHPELZX4veDIBiJihpOQvxJ2O3ZnHq2zhbY9dJgpAoFJbkMjCKiww6nJzLopR9b64lesIaJPne37Q1Hnh2TJLLm+wP03qTP/mYT5H2CrfTe0dTzjjGAr7E3h74+RKN9Hw6DIbLyp8Fg0LTuBZmiXC6qqsHRTn7eEh3NzS883/H6Ra6vIdK595n9EVvGjsOxYAEHhw8j98ZLqHj8C7aWmig1xSNoKv84M4YmuwNyzgPgT7/olNja6FoUUSEshBHwkxzOx2+uwlW/ncPbirA2eYnCT3aUhf6xXSfE2xpZjomKjyY2pesy9rgjhCqcpKQMwWwxs2/AQKyahvEPZxHTX6fAVs5rJN1RRCC8kwkDZmIzd36vB9nz2OBWsUw8vdvraPz6UwJA/+FDui2z+6cUKC4kMab7GXaZdz1Qj0kM0+LHi42zcM7pua1lCnfVULCzngFjRqNl2zm0cjv9sk5j1rC2WIaypmZ2rHgX1QjSsFF8aXAi9laoqLsU9u1CFAIkK++zPyqemsvAMMXCJ9su4vrNP+Jc9w71BhOxchAf0DLdyZjzIZO8fYEY1PBGDhx8TTc8VBFb4xDEoBVP8gZaclRdkexiVpYeRPnW+htoBiaOuYXrHpzKpv5t3tjcUDLzbliGVrqY3COljH3+aQBsk+4hYAhz89RBrc/fi9/X4pXCfPXll1g0lQeeeBLoWnXVmNpzbIdtWCK2YYlAz7FDmqbh9/tpbm7G4/F0KqtpGoqisG3bNqZOnUpaWiqBQBkWS2qP/dv69etxOp0MGvSvqcb+O3Hc+Pg3wzklHeeUtmymI2ZlM4IzUFSF3bW7mb13NjX+Gm4dcSuiIBJUgii+BjINOTjMdsoONgLQaBOxiwJzVuTD2iJdTElfbUAN19DP1IBR0JkwgijQ0KwAiQhC5we7sklXk8xMyjxm+1sD53rIddFdAN7EqXdQVP4WwaBMQINMbyYW029X0Lvu1OuZtGEMCxc9RMm+AuLTE5GbOw6ag6Mnk3v5DJL65+BI0NeFV8zZjelwu9nECbeTy+0djlPXzz1m8GY44AHxGCFQ3QUFt0OqPw/8wBcXgxrWDQ6AmzdBTCb46tnz+gzGRJVz8bmT+cuSfRwqlACFJiGES9OXSQRNwC/HctLURZjNXQeIiRgRT8hgwGuLu22PQM8dXr1P9/mHwgoJm2oAgdqzs/l+4R5QIMlqpNIfZgtRxD1wCaMe+BECZgiYeTGqjmhJRIiI19YaYro9jxjpHNtL+ncFKbJer7ZjtpguvQTefgflyadYtnAZ92SdjTtJ4E9DnmZYYiGPHprGm/1OYibL2MmI1uMcigMCIMoiJtmEkxSe5D1Ypadbvx34k9lIqbwL6FrDo6u7raoq+7Z+T031L6CJ+Lw6Q6hlqaAlsWD/K9ukvS/L3II57Ruoh+9Wnczls97qVK8ogCr0HIUtB3UDeeuTT9H/1luwR0d3KmM2JRIWijttb49mn76EdN3kfhRWG5m7s5zGYEfKuqdRP5cjxszeer18nKstNqY5EOTl2Z8gawIbx06jAAmzHCZoMGKuajOA50kTEMqrcaU2sbJxOi6XxPpTRvJ68FK8TXB28BC5WVHESbNxh3ujZZ3GS/2NWA1hrIdTqdh+EZaYYqIyN+KL3Un2uqdJ2/0nysd/CC5Q1DYK8+iSUxlSMYWXtsxnZPhRRq6HhQPeojQ6j8OmSiZ8OA6/EER09WP1CVfr1zRCN5bDCkaTPizam71oShO++ARC/8bISFkO8dNPS6msrMLt9uB2e1COxdbrAocOHWLGzB8Jh+uRJAcxMeNwOgZhMEaRmHgqFrPOoPJ4POzatYvp06e3GvS/B/x+WvL/OCRRYnjicF5JfKXzznYTGE3TuOnrnRgPurGFNVzVQdA0lMj6vaZphDUzpZoBi6DQomAaUgVqbaWUqR6gI43qq/e/AmDq8KnHbOdv8ci1GChHR4PEx+dw660vAvDx4o85vPEwph5YFuWHG1scJa2wOvTZYMivd3SGuFioKCHabKUx6KdWKOeEnDbDAyJJwf4NnkSry4ES7pnKqXFs46MVB1sMAgFMdnBEDAhbLAHJiozKqKQoll7Vdr/cXg8/HHqPRFc/pIIKkJK7NTwApCMBkLqmRLdA6MTBOKqZVW4wQPzXR4hCoMgAJ0zI4LpDdTy/r4wnJ+eyfeOHzGvuQ4O7oyx63bReXDhRp/D+tPxRgrbu9VbECAPq6Gyz7VHy8it43nmHwQMHEsrPZ83c75ErPTRMnYZ36nSG/rqWe07ZilXYwh9sqXwfaGR2+H6u7ruSx9EZOVNYxTKuISU5mrP7DgRBxB+s4qsN+0lzGWieNg9PYxPemERqdv/ExCOv4DJ0TxFueSl8/gKWrzgfTTGiaSqiIQQRR4/LNp8MZVirNojnrLNwzJ/PjuefZ8zjjwOQa/FRAsiqRIrxJ75bMhqXqQFZlRg6cgUrNtxG/+F7uLs5FTiv2+ZU1jfgAmyff05+RgZDru4i7uPYWf5w+/UB+8zh2ew7FOSbXeWcOrLjDN7bqJeRDVD0ls6DDSy8Fu74gbCi8NQnn2NpaiD3zHP4slG/r31CXvYYopHQUGQBWTAihxoo29KbkqiR7FWSqeirLwsbGg/x2Xf7ETSNL0aM4Uj4AsZqAZoKqomu20WqpYmCXW3Zkys2XUvcgB9pTFlM/dar2Ln/OhgP1xa6iMrbBsCp8okELWHih8jUlJXgKsngjP03ERKDSNEVmMY3cWhXHfbG3tjTSwg7rchVZnAb8dQHiUnWn1NJVjA010J8Av16ZfV8MX8j6upW8/PyR9i/b1rrNg1YmT2UJocDkxpGFUQUQUATdYViqxAipqQWd4WROtVGECOXpi1hcp8VhMN6XImieKitXU5trU5saGraxpDBerbwzZs3I4rif1TNtCscNz5+ZxAEgVcvHMppWw/hkES+H9mnw/4DDQVM3dHER70t9KrNo6zxSTRVYK/PwLcNRlIORlNcXNSaUE4URJpFgapQErN/Oggc1CP0W09IRJ5a/7qrrhExKpb35f1k5nWdj6akshIXsH/RB5SZDK1i8a3K5mg0llYDAnPnL8cgGvT6BaHVg4MgYNCMDC2fzuovD0K7YFTRPJxfv/2ZAxtKqC06CID9vMlI24upzMvjnbuuwmAwkzF4LCmDhpN6wEaDUeSBncu7va4r/elkakfYsOHvHQ2V9mv8lgBBv5F3P3ofQZT0eAlJjPyt/98sayBqvLNqbdsF7HAtYZ/lIUSXzKRRw9uxfICdv7QWLbSNojQQz6G1hyO/W6UpnE9SQhjR0JcKn8hIwKpUUrTpM4QIR6XNg6Fbo4I1Fsnfl+o3F6CFVZAVNFnVP4oGsoY6LodFlhQO/7hHz1+BPsPWuVICJWEfNm0xC10+4i0ihtQo9n6/jU0lViCNl7ZvIK9pAgBTvjsJR18Liq8XUfZUVvoSWLNSz/9ybvEM7lk2g0Xb55DolDvZg/5AHUXyQGLK5mDPW8Mezx762fvhMOhLGYIgcObXS4gGehXp3j6LR6dHJu/fyM8XXc8v5/UiuekbkpPdTIw9gpOhPCeM5RXGMlu7CCMyUjVkVE6ESmh+/R6MESro1KQkBt12IeWX34ymCCBoJNigNCYG83XdGx8tfgivuxZQECQF1dsHDIc6lMvO3tlqfIx89hnyFizA8dXX7M3IZND11yELukE9dOQqlv96OTEmnR5uEBX27ZhKcsRJmGkr67YtAGIk0aIsSdgTuo7L+i0GcmljCDAQZbPT0Kx7DlPjOyZa8zXpxsdbH/1EfHQdrsbBGMusXPLgcwxxFxDnaUJQZEreOgSX3MVf8HDxmEEM3VvGyoM57KsWcPVqptfJZcRTy8DwbsaWJzCvIIoDmc04VFjwh8tIUKM4pXEuxeZ0PqqayBXlC8koCrBv0A1HN5uwLxZbcBL9+9pJNlSTHxDIlKKxiHoQem6lATBww9X60tUbf1oBgEk1k04/zj7rBL7fsA7VoHHe43qW7bkvbqXS3YTfE6bFd6cpMppBjynqN3Dw0c34pxAVNYTc3FRcrnm0RBkHMfOO6Zwejyt2pWEuK2t9pyzRtZhMAUrXJWGwKIgGlTGn3Iw92oXPX0h62mX6tQqH2bx5MyNGjMBq7X5J9D+B41Tb3ymePlLO5iPbmbfrLoQTboPxN4MgsL8+n+k7m/m4d4hBspsDhTcC4PZLvFJvokEWEFsTu4EmaMiFf8Yb7DnW42gEpiaDpes1xDOLV5FW0HjMOgxhBzF1PUp2HRNB99docmm3+8/pdQdmzKxJkLhzZM8ZKhP8v/CK5dUeyxTn96VoXTSipiKqKqKmIqgqkqoiqQruAaOP2eaFQyZQGpvUYxnjznqkys6MGXufJxAN+iD1d0s2YsK+HuvJ/vYmzFHjANBUGVQFNAW0SL4dTeXWgckUxRsQjWIkv47+USN/q6GDSM1PY5OdmABZVFBQ8Puy8VScD5qApjgx2vKwZM0GQBCdaGJHr9bDux/hPrpnAQnGehy5L2BUTYTFUJdlTt+kcuEalVG79gOgKgoHBukdv2PmmWS88QL3zbmdn0LLuSMxRO+6UQQKb2KAR6DKW4Vl5TNszwrQlPE6AOM2PYE0KB2hqQrzwbbnyNY7Bt+Rhtbv3w0bjKVd28NCe00ZDZ9k49vUixDMISRRRhJUfLKFG4d8wljXTkJm/V2R5bZrIskygkXFV2WmcG422ecVYUsOYAqhG6qaLuwWan8qRUIIK6Tc26YoS8tkIbLuqgb1OJyKlDS0royM86uQUxX2mgYyx359azagtoR4GiIaRd44wqIRR1gjFJBRfDKpe92YIlRTUQCnp5KRDeuJijVhUKdjCrvIj91JeuFyVAVkexSxSckEbA6ennQejwnNJCSl8OdKL2cv+Zz+RXlkzSrGlaUbkQe+y8Zfow+C85LPZLa1DxaMbDQcIqAI1DemImqdBc2qXBI7eivM0p0bHSisR6PF2HC7dLXi+LSt9Br8HbLfheCPxWE1MlcZw6/aVCRiEYAiq0bIKJLsU7Go+jWd9PNs4n1NBNKyAbjknLPoN/xf68+6gt9fzpH9Czi49VcI+BG1AJIiYJXDpGnlbJeGs80ynJQmL3ZRJkH0IwoammwCRAp2bCVn5BjOue+RTkbntm3bmD9/PldeeSU5OTn/9rYfjeNU2/8HMDXWSdOGLQieSlj6F/1z9puoWfpAIwjgih5MsNmCqCZyznkrOaeLetZs2ccVBwq4e6iRWy/Vs8u2rKWraqvPonX7Dyu2ct+qOhZluRiY27WrsapuIRm8QvDPOzFHp7R2iq3C34LA2rcXsnOXgxv/PgHRbELVIsnpVC2SmEtlxUcHKN7VwDUvTGoXR9LuRILGex9XEcyT+OOzJwIgSiICYqv8siQZ0DSNszWNc3uY7d3w1Q2UB8uYesX+bstc/9b7SCq888FN3ZYZsXYXoLF14hA9Av6o/SoaX/y6j1SDyNpRvdEj7VvXzFoTqI3dXo8zw8ncK8cCcPv819m6ewB/n/42fRNSUTSF8pdXE65XmXLVWWiRbModBySBql92IFmMJN0/ttucImfevIL+A2OZdMvwLvcv3FTPg83w0YkfMzCrT6f9iqpw+arn2VPxE7sv291pf7i+COOrQ8FyLoPUAZwe+ivdREoA8Lcht/P4jreoN3o67BUiZGxDu4sqShJJD/+dqifvwrf5VwD6x/dncfkKvinJ5p38m1vLJtmTuPhPvWhyHuTpD/9Kn6qIcbG5cy6eFsOj3mahatIMbHUHUVsusdFI1Pg2WmV9SRGuwq2cmenCaDWhmUoImYx8s8PCwbIR3JW3iv3pLipyjFjMZ9LSrcoGfbnT6JQZ1Gcghb8qRI+sZESv/q3PgVa+FyGstyWQ8Uf8O3bAzn1Yhg7R1XRVncmiKjIltdXIqoJkloj2BWka23F5VRZDSCNW4or3YgAGaLsZb/dGssFGrr7WQtCHw6oFVJUkwcARh95mU2Ez/Z1RKKqKomgYGstxhsqJVfuxPeo1jiTG0Du/CVWxYOk3mD8/oetZVDW7eXrrEbYGNZaUNpLQWEtKTSmiQcRTbsOV5UHVYFffeg71lji9WORB60os6kAUVHYbivXLllREtaU/mRWJOCOx39tyzPw4xg6axqxt+rV6+q4Ik0xoCYeOQINowG2qx5CoLwMZYyIpGdQ4nIYcLKLITmtvmhQDAwISiqBREon1qrSJTPXq71ZsfRmq2Yro86DaHNRWlP9fMT6s1lQGj/wjg0f+scv9A4BL/8m66+v1YFuz2XyMkv/7OG58/E4xKcbJ9kl/4hxbNt/vjNAFf7gZ8wWzgV4Igsj8D88keWSARFvXSZkA5q7dj1XV+NOFs1q3tQxSnccqqXWb1WTGYupaUtkgCohoSEYLorHrmI7GRv3REkQRSZLoyofSooJqi+o+LsRgFZFFCy5nbLdlAI4l22MUJDRUDIbuSyabzYQVFUMP6pk1it5JmQzdR5ZrgoBBlLBZuvfEaKqGxSSRHtEjGJncj627IdeVRi+nHhVfJ5gISWGMtq4ZFoAuNmeQujU8Wsv1YJjVBWp7LCOJUiRYtBsnqbUtyHSQuJ9do8I0bI0jbroby7QZaKqMpoQpLFnH+Zsg2qAwNCmdVfV5vJgyhpnT38Jo1DvHI023EFzdcfksWFQEgDFTT4R12ZRrObt2Ct8uqGcfCmZgGWGacn7m4ZxdBFQnO3J7sf+SK7j/Tzch+31s+Pxjdi+cxwlnXoDNYCTY0MD+BfMIpKcy5c93UfBIW8d/yqnjGXjZta3fv527iKLCrdx64WDSk/Vljr9sKyAkVLJMOZnegYncG/MifclnypRnEQQJVVFYMv87gk0mTjp3EY4z0tn5/l9ZvnQ7532lGyXJK3dAhAhWUP0z1hPvoWzFyzTvLKLX7jkdrsH+zz9l6/yvOmy7+/mOfM6v9rxFbPVcAlipd5yGy/MTr43pHDtSU+Nly9pibtxZR5lN5MxbhpC6Udc5yR8cxyV9U7lliO4pfem2b7AFg5x5+QWcyQWUlRWy4lc9UZ1YWcpbN1yGpmmEVJVz49NYPukMUpRGzlzwNnmZtTSlG1EEI8m7TGyPllBcuj7Nty6VX4sXI2ubqAs9xh3qzxwUJBYL07Banbx6ShS3/9JMQFZZNjzyHgkCSmo9Hm8jFUIQAYFpWjLxqgtNiwQzi0C0j41RFdxzt04XzyuPpixvDR5bFea0M5nQ/zak1T8w2FTG1ye1xcE9cqiUd0trCafZudBipzwUgFAATGZCVjvDJk7qdC1/7ygtLSU9PZ20tN/GOPzfxHHj43eMW7OSyLCcxdiY/vzx0LtcXf49Hk13VytyI/2GXUETr1BW8SnaepkBo67BaOo44O2qCZEiqRi7ySx7NMIB3fXc45JxRHisJ2pXbu8ARcUWxGPIYB8L+sTmt9dRU9bMoYp87DFtRoaAQJ1cj8Kx87906cY+Brx1fhpe1GWXdw1yQdax41/9tQGa25UyS2b0ROZtELRjr91rGseUGtcr637XXrfuzfCp3tZtK/c8RYOiMjB5Ov2TJiMK4lFuqTYYrVFsTJnByPK9hNV+NG+NR0LFlJSCwdy2zmyw6EaUKEgMTsphdf1+Tj7x3dZAVH2nCBqE6msINZYT9FYSUPS4mOCedez/4nlO3TUYNI10RxMn129md3ZfdgwaxLjy3qzdMpY+chHfx5zG9Eo9ENdgtWGIicFnNpEwdSopubo67dd5u4lqqOGbdoZHhr0/Ubsnsum22Rw4JRGT00Vh8WEMtLFwAFY1e1ATrfgAKaDg05KB/NZ3QpQkzK4wSkjis/se5I9vf4Iq689f2YqfsUQ7GXoon2ffeAFbMMCeh19iDOieji5uVnOZzlz581uf8PEP82he+kOH/TX+euKr/0YYA6dN381n259DQSIcbsDtySPgL8XlGsXuzQKpS0rpK4JZBYOmEnS7kTQZRTCgxZpZXNnYanxk7d3JoLIa6q66Gr/RwLo+adDSl2gaiAIhrx8lHCLXe4BQahZ3nDeLS5vzSQvEkCBGIQkiW2J0j4WGiFmw8WaVfk8NQh1JZt1IGAukahVMqhiLqaKKd0xV2Pq+jdE7k1jzhQzzhDg5mMQuZyU/ZWwFNO7Zfw2SJJLnbDO++7ujCIltAemZsePYRipJQjlK+T/4rHI+IfVqVKN+zFNHylhU09SaZPDXRg8b/A2MGn8KE3ZtJ5SYjl+VcLiiO92X3zPKy8spLCzkwgsv/E83pUscNz5+5zgnKYbpsaP4tNcz5BbehlKnD/xBfymjT7qVLQvW0eTajPGa1znM62QsX4YjTaf6Llm7g3wliodG/PbbXF1wBEgh6OtayRFoG4Skf82wCPp6YBj8E2hqLuXhj15gY/oK5C4G7bhw18F5LRA0De0YNMfhJQdILtjPtNLDvHHGyQyKiaK2wt3q2emd14SS+dtilRpq22IM2oyMtgE+1Z+AUnCMRGqRAaAnBFXw+LpnoUyMm8Ti2vkYtTaD7Z5tXxLSBNJMc1lyyU7d+OiBPjHuj/PI++saHJHTJN+ciyGz42yrKazTpptkH7IqI0Wo4lVViykt/ZjGps3YakSiZQNHJk45+hQANK75iIfyhjKovoCYoL5sc+HqpRzqlcWqviWUOWC3Q+DKg4vZnTG29biaEt17EvC0LfVsGD2DlLoKhlis5Gr9GFlhab0PqbberPlY1x8xAAGThWC7BJGXxsXwVK3uMToxJ55e0hiU4IYObVVlAVtCgGBAd/vn7fChIfH91yLg5R+rnmgtG1Oqs4g0Wc+a7Pf62fDTeuo/+BC30UedSZ90WGJjwWxBljq+09srfkUCKm0nIQgCe9weRiOyfftVuD1tGWSbi7/EZBPJvGMUW+YfJLrIgyUhmW2JDXjcHiZ5TUS186JJvcfRVP8LjpuuZeXyhUiKymXPvIxSH2L7vO9RFYVDjZsAiLKlcVVjIr4vD/Nn9WLiJ+ZywZSLqPfX8+GNkxhQ7WTrWc8ySpnN8OA+Non9WBV9AkcS03i44F3Sg1WsSB5IUlk1VXIiaigJz8FHsWZ8hOK4im3ABwkn0EvMZNVVHwFQ+sAa3DEhTrx/Zmub1931DK71u1lwy9etsygn8ZSl1hDdSyZKK2R/8mCQYdqmPPK8OmPEKgqYBIGwpjHeH2DTkPGY7E6GlBcwpM+ALp7G3zd+/fVXoqOjGTDg99n248bHfwFcRgO3ZCUxOdbJn/YcoSCg4K54nw3NXyFKBQjtcnnVr1+M44Ib8PoCPLDgEKmEueZ8XU1y8eLFqKqKyWRi3LhxXQYExaZlQkUYv6xRXdfYOhsQhDZGTDDiHQn4fIQFoy6WpgVbywIIYQ8STsLeMGKY1k6gdZAVoKZEH4wCQbnjuNYW1oCq9pwXtwV7NrzC4CWP8jagFsKv0kncHZ5BvCZw9YzebNu0CVXWqPF4u60jrKqoAtR4uzC8IgbXiYu/4FBmX/LSc3n+zfexhMJsGjaOh6KNNBQFcUkCkkcmZBGojVAZW7KittgIkqBicBjJSHHgDUSojJFB2x8K4Au2nV8VVcI1TZHzt6xv67EAmhZhszQHCRaWo8kKyLrSpRZW0BQVLSxjFqCmoInKLW002fYeFWOlPqguOLyGPG8lRtFESBMwCxqNssLiA9uorD+MqgT58Ug1AiAJAgY1iMsqtf4+M9Do1Ih2C1S+mY+UuAHTyQkIRiOKILHu0AIAHj/4Gc3hRmIljRUr+7ReX0kw4cmSaJhoJmHoYCRnNJItGoPJRfPn3yEUeJB+1RiXfRjT5N4YckcRfuZjAPoUFNGnoO12BcxHyLTEcnjrQWxR9kjr9DihFuzsPYSajN7MnjWxdduaxQdIW13NMzkBjEOu5C/TJvK3XeXMleDidgP+LUPSOb0plqCq0ddl5ft1yzo9MubwSYQNP5E0qhZBEFCi+0JDAZfdm01zSQWe2IsQvvuK0tRJpPWdRMATomzvPqwqFI4aSTKQDCwZ1BsLEn3SIzo9ikKzXeXh7d9yx8DTyK/fi1So69pM6neHfm5RQ1GkVsOjsuIKHLVDGVMRoMplID7KArKKLOo5apIGDyJeVdFW7SSu3XKrEArhtbnwhPRnUpFE1jz5CIo5horGMmKdqURbU3BZUumXfIL+fLsFzghPoTgUpLq+krqJ09F5J824frib/cOiuKXmchYmn0ZKWOQCKYZpo2biMQpc/+scXl7wHs9Me5D9FlAEEU1p0wpaErOO3pTQFukDvqiOk5jo/dsRC/bgbzJ3yMDt3GWBFgbyo/rmAn8QsyBweoKLNwdlt9ax4Ls9HPDX0WDXqf+nnN59gOvvEY2Njezdu5dZs2Ydc0n2P4XjbJf/QlQ256N6ttDcvIvmmrUYqo/Qa3OIzw+OIGg0MOGCSzkQdvL4LpFnJru49PRJqKrKE0880aGev/71r51EZ17+Zi3/2NqzbsTbxpc5Rdp8zHYqWiwVwdm0kRU7YlUgTFPXSVA7wCvK3Pfmyd3ur6vaQ9xbese3Y/xNWPcX069JFzh6VT6HrBmPsaw0j28zUo55rj5VJczM29pzoaY6fLLG+WvWERUIUBYXj+AwkNfrYQCevKjn+BQA0/pqxObOnp9LzNswC7p7/prKPkjRxxaGOxa8ioa9By9VnaGRq3L/iiJ09LIkGlSq5bZ7p4Zi8B65v/W7JkLwxNRWw3Leag8Z/o7dyVpDHnkGnTp6yHmIXfG7Wvf9MT7AAKtKr0Iv2SV+RA0+Lh1OrbtnRV+brDL6hOmMuete5Lo6mjfvoHztHjRZRt6zA83mYI9xLG5n54BpTZMRCIMgUxkdTcgg4HNK/DzeCaLO8KiL5CuyiQI2SaI5ECIkiXz943Xs8A2i3pDI0V4go1ZJZko+SYOyEWhJeCciOvQg2YLvL8bX7EYT+hCTOqrDsmb7HCCy5MVvL8PQtI8GixPi4ondq8fAOLJzCbibKVOLWTxBD6Lt64jl5hidxVMd92cuGabnPnlp9Y2khHfzjngrRm+Q2WvbVEsBDEk25Cofu10iS0+qRkQgoIh858skK6+E04VqTKZoTnn5SczhIKFZlxPw1FGbv5WSKDNeiwlHIMTIfmMY+MD92GPb+urSqmJ4uYgD42v5e/Xr/O3vbRmQN+WkMLv3+RTYs1u3BWal8eKqPBIsb/Fs85WklVeT4m+gOHUmCalWQkKY1SzCJIUh9hdsosI1UcMQBIFT11+PbAyS0KsWDY1mqRHPs29E6j2x8wpW5LZZlv7MT+Mm4z3rHBB1Flid143QIo8eKew9dBCbHOKlu+743ciS/xYsXbqU7du3c+edd/6vBpseZ7v8P47kqByIyiE19Q/QH1BkOLGKCw7tY9fWPLb++D1fuk4Eaxpv7w6Qr+3jz9NyOOGEE6itreXAAV2/Q5blTsaHITYBaOLyvmayXS2KlBFWRyS/QZ33Ig6XNlJi7sV0308AVDiHkGiwIDW0GSWSUE9wRAKaZGh96VuUHzWg+nA1y2q9XDImozXbbevOyB+rjxxhb6ORz168j6i4NZF5v0Z7nslF7gruALYm5jDqlOfQTlL46vm7uSj0EbcZvqdofwKL0y/HFla4K7brIFqAD8ob8JksGJyxZEwY32WZgqU/kiGZue7lv6EqCttPmEhyQx1inUZV9AEaYvpxxmYvh2I0Jg9LQQNKa5rZUNCALxJyclaumegxMdg9Yewt1FdNozFUSq/YNkq0/4F3IKEX8Rdf0tlzhAiigOoVwShgcAi6FolB1JfDRBHBKCFIIuriemR7COtpHWnCLfMOraiJr7a+yLbJUcT1diCrYULhWpJMRiqCfpCieW5xHjWNHdVqBRVeS7SiabqIWdnpRpwhFZMmI6gamr+ZkY40kgMWvtuwGYvFxB8SemHwZiI1FmHcF4frUDJVjTLzBD0Hz0BXJbU4OfWWyzE5nTqrRxTBH4JyHxvmzaPR62HXxjWM4V4McXHEnjKT2FN0t3tzfjkr/74CXzCWNHMFuecOxu/243cHaKiqxWRxEvRrhPwqfsWDT4kisyDIutFOFIt+bRNNbe+EBoQjhtvg6CqmOA6zviaTpcKJLVdB/9crUL0rjqRBcuRdUdHQUBr74a0OEvK7QUjCYB5EwBtGUzXkUOclNYNix9ncl7ApGYvjEAQ0mg1OKszJOGuMnHzxGkrrjRCM5OyJaIU4+3/OzNS2Z9bvL0IzqJSrcThoG3wEo4imgVznp8AusC7ewBqPDRUBVRMx+f1kNpWiBqpopApTWPfMaSsXYAbSBEitC+I16nRfl7eUqhe3cTDdTsbJvRjUJx41LCMCcW9+wY1Us3pmBp5aU+T3KR2S8wWm6yqcyWl/45AhEZexjl+1oQDEqSEO16s0oAIzCAFxjjzGxBbzdf1ONCDDlscQfy88h6LRUFHaKeyKy1d26TXVAL/JRGFyKkuMDoiI8IWjHbT3s5pDAS5oqCF2wKD/KsMjEAiwbds2Ro8e/btkubTguPHx/wIkA7jSSB6dRvLokzjx+ps5eV8edy8pJT05hq+2lLBsfxV3nDiAc6el4HM3UVlZicXShfR5JObh/BNHMSIzpvN+YPPC98ktOkSuTxdZWhV/KdNueYvQM9ORgLChH0ryFISYLHqfP7DbZhe8/QWXD/mJwYNeo2/6EKymzi/K0HInZ7+6m1zfEM7OTWgVRBPaUXtHNizDL+xj1M3b9Z8gSVz0l1fQ5L9R9/K5ZNW8RzJ9sfcawy2jh3bbniXzd1AtNyG769m98muCYpA4fyJii+dGEHQ3bmSJRJQkRm3Q87SEGhrIDipsfmclpQcVpHiNp26YxEtz1/L5Zt2TNCVR4Z2bZuGw/rYOYfNj76NmmOl/9Sm/qXx3aFq8DKsjRNKorrVH6gQV+2Yrw1OzGdA3ucsyD3/ZgCbrxsoM4yE0wC6E2PttRw9YY8ZuevXaoX8xAAHwhs5mZdpKLk4bzHhxL1j2MnOvHi/xffyjuGJHQoFufFRXxoIVsnKnYo2L05eQAMFiIaConHnaefx003U0upvw1TTqS0uygqpqaKrG4R+3UyqnEi9UMHhaNrnTOuY2KTvYgMkikRCJy3lg/l7iFlXx3YhcsmM7s5OKGpsYt11fzwldugA+mcbouFJG3Hk/lpi2a7Xojc/Zv/orTj77my6vnxIOs+ux22n0/cSUF5/mxb98iz0ci9/RiCZp+pKlCN6glwRPJsZwFLF1uiLlu6n9aZL0a++fbaRo6CLUeDuisYkv6s3cd9o2JKmjUT3QFU+ouYBDJ89i8T8+AXohWorwKBrNTgeSM4p+JUcYULGQu11BZNVPvUvCl9qLXwsS8Ukij937GK/WjkCS9efV72pkX8x6RhWeSkX0PEz1qzGZS0mPFRhYHcT1wX5WxRrwOcMMRSCMgcTJAZT0KjxLMsioa2ZwaQ1jL3uX0dSw+gQ9KDShdAZuh0y/5AP0yz7AJ/v+wMuX3kdsrN7/XPT6+2wsTSHO0sQj6XU4LGEey76EhNGP4q/axNbtlyCLGoKmIRtF8v05WB2xXP5YR3ZQe8y+6Gwm1R7m5bMeA+Dg13NYMPdzrnzwCRIidNpVC+ezCrhg7L+fXvt/E9u2bSMcDjNu3Lj/dFN6xHHj4/9BiJJEvyGDWDhETyJUXOfjoe93c+dXO7n3m12cMjiZ80els2/nDu75shCTtYY4m4PaZoGMOBNg7jHOwrXjHQB89xRjMluZFqHbatH9oXobsmMo1uv/dsx2npazHJOhmtrCi6jKF6kODiYt/VqmDjkdQRB4fdkh5m4rxQgMtWRx67lXUHGohPxdJRzZUU+610wfk5koaS8GY36n+gWDgZibv6Dx7zN5qOZBPFEPQ7u8H0dDEwQqHIVsTNhIqi8VAQHVITEgYTCqoqEqGqz7iRRfZ4EsU0wMJmDqoxfyt1veJc2k54r4ZGsNYOL9C3M5cVS/Y16TTm36d6yKCmJXvOpWKLI+AzcYui8zJV1ieUGAmwdDL2cvvdouZoPBoL6s4nTcgaZ58Xjfw276gTMc6RwuGc34rE0sLZzOTPRB+iE1g6Swn/Nj7iIheABVyQOO8P4t1yIA4XaUZlUQECPXQzCk8tHD27poqRU0lbOfPRNLXGe37/x/7NDvYwQtfqaj8jlS3NjEk1v3skDUDZI4dyNRcYMpn/gCqb/eh/Ef/ShMOIu4Mx5g7YKl7F+zgmRLM+qjMVQMfJKoMSfizOlP6ddv4Nr7GkbNwwijG1zw1qcjcTYnkHYunDOrIxPhrY++xr/NizPKSKjOhCdLpamprb1/2L+SqzOfgkZwDngACQ1vRT6OpFxkj4+gr5z60o0YPWWEgHpPE0Mq9PuleJORUHCERYRmDZPhe6LVdfgLzFj9QYxRBraai6mpuQKAV+csoj5+E25HmMSaYViboxnqnklYDHLGiiO4mkNAOW/c6uad/tG8EJcFmyoZWiSz2yXSNEMlYazKkMZZ9PlzOk07XiWUFGRcXjPlsf2AOkwBO0OveA+AOUtuxiWt5MqBX3Oo5mTGxU7X77sGY9Iq+ObW61m95u+Ew7C34WNy1pZyKLQCTJASSsdqSUOSbBSKtb+NAdYOLe+Z0C6ouKFON5CT0v/1pc//LSiKwsaNGxkyZMjvPmzhuPHx/wEy42x8et048ms8LN9fzWcbi1i4qyKy10jIl0pFxBOaX9FtNQCsf+8OJsi65LkoShja6XwIbn2GaGxa2+WxRyPXcgHFoTcxJ/+D8tr9CMFFqHV38MnCd+hV/EdmeWqY6jrMT2lFNLtTWf/dNpbuatQPliA/CtZocLuigNo17VeyO3Hev5qDr5/CVTVzgTu6bY9OclQpdZRS6iglO9yfd699oEPA1v6XHwRgz0mRGXWkj9trTeGz9DPwGqMotSYSrfm5/o0lNKkmRsWr/5ThoefnOAbb5TfVIyH0EPMhR/LZGEzdU6eNIhhFjTsuP6fHUy1Z+i3BYCIzZ+j0ySVL1mM07aGu/kYu7/0IADk0MCnwCm5szDTlE2vxU2+14vMnYzKNQWiuRaCB1EY3jkCIAylxeEefgCunD06zmeJ15Tg8LqaMDOuDjCDo9pWkpxRwJMdiiYtCVVU+fWg9ngZdrUqUhA6GB0BtrMjK/jZ+XL+Vq9ITWFvbQEjTWK9IVBtsOMJBhtaWMPTgHqTpQ0k9+Y80pA7At/gJsmvmo344n315k1FEjedmNPAc6Wzd/xD+A39FUTXSAY8hlTrHyVgbNuKgDnljLOGBFZx10iWdrl9LpuiZf5zAOa+vozlieBgcRmRPmJsvuQ/qoUWw7ck0P5sPngYHO9ZjE/XP1LmTOCllPBd6pzD2zj8w58nHadY0bn76WXjsfACs91fT+OFIRLeeEqHZCFFhqMnbjCRAhdfGuGvhyQ13t9Y/a0Ube8rsysds6MWEiZNgYiZLNu/n+uYALwolGJvNFHn3I0TPxe+yMPZwLZ6k8SipIaCOkMXLpp9HE515FqNykmlSHqO54i8dlj/QhNaEmZqmYTTGYQk0s6XUS8XG96hM30nyCJU/T4u0b/7Z/+NlEjWS2E2MZAX3+7zsPVKABRWjsful2t8b9u3bR1NTExMmTPhPN+WYOG58/H+EnAQHOQkOrp/ci6I6H9fMe5GSGiNy83BG9K1kb90+NMVBrn0ig1NdXdaRVvEThWImFWknM97alhrdv3otVv96AISbV/2m9ggICJrEpMGnAqeiqnewfMd3JCmPIGa8SIlTD1Rs8VX4AKPpfMKhNve4KxRFtHkeANWP9dfT2euL7h1CSAYIVZQZeg44VQUYEB7B0qs6q3i2wDfAjqXQhzQ0s0PM4cPGawkJJs6TqolWvKwJR0OJ3qHdPOOfMDxa8C86PjRNQxAlFG/32YVbPB9GY/eeD03VevSGtSBm2XrsqyX236nT+zKsGqLfxImPvtlapk/2Dk40Wpi991I8mplY/CgGP15nAQftJjaPLkY2hSP0IAGoA+ZDEAho3NSsq2oOub5nBsLcF7a2Gh6xqXYkg0A4qDJ4SirDZuqz2a8+XcnuJoVdCRK31wYAKyYljFFTyQh4+PXkCeQt3slc2jw9MYOnEDP4Z+Tn++D26PoVIalNQ8YtigTWRVFeZCP3rEr290tgzLUf8Pabw7iyJsxZjw0gK/lEukKVR+ATu8irb65tjdN+/dRBbGzy8OmvRZxftofx1lz6kErfq3ZTuX8peyt07keacAPl8mw0KYymwS9eGyn2i/k2PoXJxgwkq5nDpm5E9jQVTTQxethyPsxbRkFIYPa1F7HgL59xpbU3po8sDM3sS0qfNJaWryTsUjA2SSScN4aDSf3ZY0jkq22lfF/RwC8WGVUUMDQ5CUdVIUTto+6Ai/p1sRh6lxJVuQFTvUjhqGhko4hbbMBdqrOW/EoUVqktAzLoZpax3cMnikbGzNrF5j/rk5zk0mHMl/Zw9rA5pKdfonsxjml8aB0MnNYs3hE21LezP0RG4IJzu0/w93uDpmmsX7+enJwckpO7Xj79PeG48fH/IQRBIDvezsobHuOXkl+455d7qDVYMEuNACy+6vHWspt/+Jkx2/UZ0nbbRPoptexKPo8J173UoU7Dz38EEcrkV2h8uxBNPUzIV4XR0s2ApkFRZoj3cm7lmSWfkhUu4hxpCxIQDGdicrYl7QoE7NQ1pSL7ba2GR244jX6ynVg1ll2+3gyNOYJfiEJqjRuJDFyR/mVLnZntWg4//rijNXD26KWII0aVeHeYkx9pT5vUiNFK6W/0ESOZkKaMJeUCjQsu65gOPfSAzq4pSzWzu8Shu7eFEAYU/jF/GzV/fZgswRsJuNVQgiEO986mOq1jFtH2OEEOE/Prr+y5YFxbR9naqbYEoIok3HwLCdO6VrltEbZSGqyUPrim405B/ycl0vH+4e31iKJOnG3xWutXUaBeUbAIPXcXV7yykL8s7FhG9OsVpRdU428XcjI5bQOT0zYQCln4dN8wQlKIYNMMigxNaKZGBiRfSJTNRUsOZT3WR6/Lv8WNNeTknTu/1/POaHoJTY3cc03X2ADd4Aq551KbH0Y0mjEYLWxZYGHHTxZMFivu5hBTmqKYFK+yv8GBIsMIlzdCLRf4YNEe/Ae2Ayn4P76H1SY/d5oixmmyBZuaxEZpDXV5dma97MKqaNQJiXxx3iUwAW7a/QFjbDupeT6dU4w2EBRe/OQJ7MZdJNpHUlgnUuooZfw4PVh0WclgWkRjpg5OIiHJzi9hP8sOVKMJ4LnoIo5sqyOrTF/6Sx4wi+QBRyh99w+klz9L2ZT4yHMB0xw+Du+KJTRsJG8VHmbsvfcyqKAAZ7Ob3a+9hn1/MunpNcgfP0RUcQHfFg2mZO2fkcxj6Bss4/31ulE/D7iw170MUHrR3ziEqnKZgoslRvU/hZA9iopKC9YoldubasGmPzWnbvVS7qnm28R+9G3oh0nazf3/+BhFkymbO4aMiiBT19cjCyDfdwAEgb99exsTUregagLbquopDevLagX1JrKjitlV+iOy3IQseyg6vARoU/491+TmoNdBfe1BStVY4psUjuzbo3uSNAiFQpiMhtbvXkHEUFdL2ZpfADiyTY/dOrhlN7aaAEeq6zCIIoIUS96uCIe7JWg+8u51Sq7QSQyxHc+3dZOGGpkcoUZC57VIXVrL8o/eP2kt3yP729I5dH1ss6eJ8vJyLrvsMv4bcNz4+P8cUzOmMu/sefxt44ssL1uBWjuGB656hhkFa3C664n2N0NkXBPQOGgfiXPYWa3HN2xfT2jJ0ySJpXjkyTRK/XT9gIAPxe/BIDo68szbvYeb6MUmctDMInvMQ3AHnExhCx85r+MZ7sEQiexUmpM5UnUe3/Xqw1mlawkajNTGZDKtwgYSmK3/oDSg99krD7zKjJtuJW1yR5GqDx54iPpgMy4E3PV1AEgGA47otqDaCXVhepeH2BNhO2gauAOFDDAWgwqaMZFGTwxGi65zsnxFbwAyU27mtswoXi1OZWOJ7jFyqT4mNOZTFpNCSmExw/J30dgrByxmNEHAWVJKoslAQ1Zm5LJ0nqnlZ6aREaXomgy0MY7aOjUNcX0d9Su/79b4aGEXCRYZY0ps+0NbPUSF3iDf1TUzKdmF1SC2asi15ATRNI1QhZde3bhh7vtyM1/v0F32Hw84hXMK17M+sR/DG/biHNGMHKvhGejEXhfCKjZh9yl8kXYqYpmNmjIHXqcXV3wUG5MGYHTvww48POZahsamd3m+Ww/PQqoYwqnpIxFakqBF/hdEfell78/bCPsk4tKTkBJ6EQr6kYMB5FCAgKcepSGIqgRRInlVGvYNJTEy662MXJ/WXEUk45O8WGrmsio+Bkxtg55dhTWMxloRxhGoAQSUdveyaqKJqLBIfMBDQsDDYaORX5J+5fyC87EcmEJ/oD5rHp/t/wyAi8IP8bngxC/Cqr1VCHvafrfmNDIn6OWFgJudjj0cWlmGoqmgatiUdYSTLMTUh2iIbfNurB6sM5zSykpoXrCQ1tysb7xJEJHKaheZztdBgBK//i6M8m5AbhdrI0ip7JNKUWpc7FlZQG8hkfzyYZQesAJhriFMwAA5Y2I5sK+MRMdBVE8s+QEbA9GF3rTQRMxxaaCqpFW1Ldm4h0wlxqrP0j/cexnfHjqLsGLEKxuAljXgWAbGHaDmYCTNBDJHyu4k+6QMqsvH873xbHZnnYqvXIRyH5x5B0NKD1P79bddPj8A9B9OY10lX77+YofN6xZ8ii+zH9idyMCc7z7uvo7fIawGF7m5uccu+DvAcePjOEh3pvPsxGcY+o8XGZJv4KqNeu6GZrOdouTeZNfXIFlN9BFDIEiIapCyOa+g1Rwgvf4LAAKaA9/MGxk0XRds+uXzxWyZ/w03vvkpzriuWTNzFv+MMRxmzdh+jNtRyGrLVFaj51po1qKI1Re3sSce4WSzzDtRMXwwWU/49UyjgdhpIvVz6jrUOT3zNtZ9+yFjdtxDal0hBi2EqGk8aoE9Wj/6znyB1656CIDMwcO48OGnW4/98YmlaKLMvfeehN1swuML8MLzqwG46fa7SIqJ4uWX/4Si+fSMsREUV7zJNyFd40O1SFwRkLhJjEJzOPAsuB9UXc+j7/sfEJemd7Rbxo0l3hXFqQ890u19efvWM6geO4ip98zutsyeEwZ1o6KiQ4usZZvTAsTfMKzLMonA2C73tGH7G8uxVnRtfNQ26WJxk5IULrr+buZ9uJtPVJVbC96CxmRohFPmHcFvT6TftAbcspN30m+FdPRPO0Q7LFDXs6y8Et1EgXkxaUMVJNGKKFkxSDYMBiepqRdhNLrYt+JDMkemcN4dT3RbD8BXP7xG6RdLuevuO4l1JXRZ5stvHuNp3xKe+kMZT5it/EX2kzdqPGEJqqdfhNU+lMIhTqT+fkZHWTEPjCV94/s0NTagnDYD7xl3I1oS+fLnO3m3dguLT1/E+69/0Fp/RuMAXrpNfyZviP4Ho0sauHHCX5FEkYQEO+nJjtYZu0kSeXbng3yTsAiK29r4fB8L+Uc9CHW+WFaYfOR9v4yYNcu48uSHuGv7VwyvOYzPJmHzKTQ1OlFv34g3/wjT5l4PGHnrVBsbB+n39MLl/YhTVbaqNcTX6Vo6tYnr0ISOqQosMjQX/8yomR8gGkJoqsR3JdEk1RVh94aY1uiFovVQsgFRVQilD8VUugsx9zQCNTpLbfSw56gPxnLfhOcIK4qegBINVQmQbB+D2TCK1399GHuTg7smP42aFKbOVMJGh5XH4pvpG2NDA648IKCZLZwxQ+9L9h46QkFJKZPHjCbG5UIQYP5Py7DYHJx/1Z8AOLAjjz07VzHxojswOWyUNtSQ3UtfLj3mCk47L6E+RWjxSh6VkUDQ97UXbiSSPbjFS6tnExY6fBfalW//XWxJ6CnoWjErPtnPtIuG/NfQgo8bH8cBQNm5dzK/aA1iVDoq4L3nccZcewGiKOJ97hzEhk0Yvfsxmn0IP29qyYeFV4ujeeRfSTn7WtpHFaiKPruResgps0myETKayYqJZveYPry6Yx9b3X6KNJEVhpO5wPBla9lHXPYOxwoWA7Zh/bENg4CnmvL3f8ZUmcFW+z52NG1iwnwv+SVxHY5xXFiGyWLljs+/R1NVpKM0TiyT9LXz9Wth49ZzCfkciAKEkEiKiUSOCxI11Tl8MecJfA1XEgjWMnD4IiYM2sGcnMsYevAAqYFowAIGq06Djhgf9qTotvZrGtq/QXkwJtWLvXY93scmd7lfCwvA06B1n+r+t2B7Xgh/2Myvjy8hVTaQaAHRpPesF3sVJmElNWCm5tsSJjpd5DQFcE6Podcb2zHJKiJg91aTd2Bmhx45S6xD1CN1AAGLsZE6emb5KHIjqiZSVTW/076CwtdR1RD+ulyaKxuP+bs0pYXp031QoRoJ+hUFATkcYPvGH3jrPJWdOSLwDfANLq+T3g0TcI09B2u8QG51X/YWDCEqYTv+hiLievXV1ToFgfT4DO6990HWv7qA5D7Z9D7zWqxmC0UVZUzb34c/NOQilOqu/jKrwI/TU4gySggGkbqwzKeZGlZ/MuvPnYckihyp20TlgetQVRui2KahUe+Ppd8ZU+l38lRW7/0TNZ/uZHdcDsNrDmPzKXjtGnFmLwduPZn49Crck5JwV9nZOKi5tY69g+KZtDcVuye7dZurYQhf28I0WvxMMB5g1aRpZEv7eFB6G1fTWBLSZ3DE8yyXuwWS1cVM1/wI0cBHK1vrMJXqrCjXd22idXnZWVjVMBOSM3SNFFU3cEwGM0bJAIJAeePLJBpiyR6o67rM8e4Er0Y/GaZbYyCuNym71xLtimb0FD0RXEWTh4KSUgaPHkNSkr72t2D+fAIBP9mnnaGX8Vtg5ypyRw8mITOZUcd8cn5fWLXxAA67i0ETuvYW/h5x3Pg4DgDC5Xp+BrVZV0scfv4prcsl9ge+by1Xf1kKriw/Pi0G84PbsUdFY+9UW1v0ePtkXEejoV0elQSHnScnjWm3dxKri2cSPnwDa8WzSPIMIkYQ0ARYZ9UQI5lww24PFa+uxeBNRh5UyZ7SX7hipYoHPaGZFCuj1OuPefOvurv8aKOjBVJ4EopxLapsI+xzIAAxcQpjxuSwe/cS3O56mhr12fGhgy1S53GsWX0FFwQspMQ/wgajjW+z69kQfQK3RfchOOoKqn5ZxsAVBax4+AaMJgsiAq6Al7r6Y1CLfgPSBunLBkGf0uV+TTCBACZr97LyvwX+sJkUo8BYv363A2EVn1VX5oxHxGAAKaShRZL3JQiQO6cBBaVV4tqQmsqohZ8AcPKKpymgNxJ2FAQURMKqTGNES8Sm1tPJLRKB09EPGkuZMX03suxDlt3IcjPbtl+CLLcNnHUFx5bPVcK6YSj1wGhQ3G4wwIuzb2ChuAe3WSU6SeS0xv6cMPws6nw1vFb1KTusPzN27unodJQhAKStfwnLRi/FjjjCvUa1eqlsNhMjr5tFSA1TV9tEQK5m0XP7sWjZHLSo9L53BHvnHSK5JsBzipuWnIiCqmHXFCTFgD2S7bjywHX69VWDmMMCI8Z9x/jX9tBsjiH2UBVGUWBDiX5dvuh/MkXOZOIdS3k5fjs6s1SnlPbTavHl1jAhYSpNoQaS1XxWsI6wEsMJhwUE6whkoweLpZYzowvI6LOFBtVGpdnOXbyApgmMOPUD6uuL4cCzjPBLJAUzEU66QmdtaSqEvFCxAy1zPH61ATkqgZY1wLuWKpzYNJ6mZ9pUcAHaP7nv8TRL41a3fhcjZmv88rvAcwgcSagDP+iQ6mH79u2YTCYSEjp6tmzR0a1/t1Ftf59S5D3B7wmRt76C0admIfUQNP57w3Hj4zgAGLB7B/49eym7807ClZVI0V1LXJftSKZqa4DUBT9hiorutj4tMmsRuxnoAab5G/jKGs+sdT9R3GDH0Sjx47kjSLTrQaNTMmegZRxmbEkJy/PycTrsTB43iszVu/CWVlE8fwfKPg0xYCfqhkSie83gmgW1NLGdlK/eJHqYrhMQ9tZzeNQJSPTMe3cF7dQbISE8naysaPz+OhobFX5akg/oOiLOKA/9+6Vht0fjrztIY2gzOYEyrm+XmdWgafx0/l8wGvXg2LycgVTvuIfYn7aiCTqrJmDW2JbkoSf5MFUN4PcX91BChyetN44butK8ALW5EZ7ZjaGDbPT/HP2ynfjL25KyCePTGHpO92vLDV99S+W8I3qwqD0OzVuHOUfXm9A0hav4kHj/WIad3jF1/MJ9b/JgLVh6oAaLgoCKhiBIGI1OjEYnkMrECWvw+wsxmRLZ9/k1JPdP7HjgY+0YXPcXgjUGVZZRRA1J7N5ILivcA7kwx7qLgXU2ZsWexOUXP4SpXcbezT8fZm3pWsbcEqezVESwybXsrr6WMatfI9NTx+ryOobXXMLfXvwcY0EcBrUj80RCN4BqZY0hIY1eqoQxqFE4eQh1vjBqWCXeauTuuQIHg5Ggx3YeItWgYAnbsMYOxZvdgD/TxW2lEQPXpCGckMj5moU7Jkwi0XgNda8OIF5VWyNUUqxucENuocy2qimkikPJTVzL+UkVjPzkC764yIskWKgTQ/QeupAfqpMZ6XdwV9wLAAiCRo3qRg3rDCODAAFDMpxwa6drKhCJTW2HmQs+xWsvo26C7rGUIoyXsBpGU1UETSB7lZ1hwT6tx+RGXrvocMTo9FQRkhVqG3SjXFEUVFUlKSmpQ+zZiuGTyEvO4u8/bUJUVQS7HceFt3BZj4uYv0/s+aUMARg0Je2YZX9POG58HEcrrIMHkXjvPZTddjvzv/8RITubTKOBIQP6tHow3I4M7L4K7OkdZxGqqrL9pxIC3hCCIFB2sBnR2JutS7Yy4qSRmG2dVT2rqqsJ905h73YjhtJG/MAIeTNDg/XMjIYtQZn9DhdVMXFgjIYgmH/eDCYz5grQqlwEjZXUpG9B3BUNu34k5v7Z+trryh9pXLW49Vym1ESCAZVfXpiPK71vl7+/siYdn2Mi4eT1xKX/yKf1ZmaOPI2QpwlZ9iMaDJjsViqkKi4Zdi2/vHU5/rLLCWi7GByvz7JnZM5AQOCTb5cgCCJiyxrtHU93CLZdcegnXEH9unWX+EnTwF3Rc2cYsFkIRsW2i/s/qo5gmKC9jMPl2zCv3EfrejRiu+h8gSq+RcJJLEct30TGNsVZT118GnsbBmHQzJhLPFS8tqNdNH7HYzRyqB1/J+tCdZj81QhoSFosyl/fIkk+yJCToda6iW833oAgSIiiEUEQ2VCpr/9/vPYZhkX1wSAakSQjkmjEIBqQJBP13kYUJUjlpsVILieiaEAQDQiihCgZCIl1GCwaPm+IvEOFEVKPQEq47Rms27qCUNJoaqrKUUSNw+WF2Ay2iHKuzvgRBAFJDVA9NgPqK/lrwiXMOP18BFHE7S1H9EsIgoiiiTT46tHQ6JOZ1k59N4Mdu94mrIoctEUz/tCfEUMxeAK1qHY3XmOYPlOjKS4NY9nsjFw6jXxFRX1jJ4OS7YBGOL8IZ0wstZKRAl+AGsVPnSlAvruO7z6eyhGjiz1RZh6OHYut7yWUF+wnKznAXlw8GudC1mBdaTWrHGbkOg91hfk02ezkqA4aASduDGgoiFSY4/mw5lLCfjhFcHJb74UYD+l3NxheT9AxnIHSJp5c/XcA0gYs6vC47KveQkaTbuRLSvB/FH9gRsRuDdLvxJO6LbNv1XxM7YatltoD424HuwH6zoI1ha2y4nIkY2NJSQkAvxaXce2eAuJECWfQxyVSCEWCA35YG5dM2NpZ5fb3DDmssHtVKf0mpGB1dEOj/p3ieGK54+gAuaGBQxMmMv2tthnprT98wzU3XU9qv178MvlSEmu2Y7z3GXKvO7e1TOmBen54eUeXdQ6aLDLtsmmt31VV5eNXX2aPXyYvOYvKYgN1fn0WGZiShEsVaLJLDKgqZ7xBo3d8LBNzs6kpKeWzxUuxB330Ky3BJzd0OI+kqMzaU9Dtb4vK8uEbPpifmu7utgxATN9lJA3/GkWD1R4Di5qMKFpbR6cgcJ0lHnH7ZYiNvRAQ0IQQanvrohtVjFZWiyYgInLOnX1I65fRZdnXbzyNoFvg7jk/dttW/4vJ+DMGEnvxii73K41eti28iebkDYiKhbY0nxoIbTlyNEmfrUqhrvVdFE0j7wedXm0W6ZiLp4tfKwBrpDArbGHiA02IqgqSRJPBQra7lPvH/oNgOshii6NAQxRgrcfA943H7kR7mRRuTwp2u//QD1l4K3/bQOKxyHw7o+w3le0JifVmTtvQnb6Chsl5KeIxtGZqRJXZUd3/LiXBQnhkXLf7AXJqyshP6HoWfMW3b2JP6Ezvfnv8mWBu8/5MX7uQ6YcKODn7XNxJm4kJ/Uxs8172mk0sttn4sFxP3hYe4OKTjKu6PNeETfXYAiohzYgm6AsksighixIIAlprrI+GHR817u8BkC1NHeoJIyKEHFhUAU3TCGtBwuhU420xJu4cn4ArpGJUNYyCSIVZYHB5EacfPqgnm9P0OJgGu4uvRk/nT7/o53mMl1ER+OiUHTzdWI/PLHL3vAYcLWQcAeTgIULu+Uim2MgzHyF+twaFtnwHENtl7e5YpuVYoYvj9SDSdikcBLE12FSvk8i2o44XBJSwitedzJXPXEF00n/ecDqeWO44/mmES/WYD6fXg9uuz6fXnNabc889lbrXPmL4h89TfubJhF/8C7QzPg5u1NO1Tzy/N72GxRMOhPA0VLHorXL8zSH8bi+b1/zCuvVrCUr64OIEpsge/FopjSYL2TUZGOfrRsiokSrjbzytY+PSU/B/9RFHSgu57vOvO+xqeekX3XohAUXhD69/30kTo/pvZ+AEbnpKj4I/2urWVI1PHvsBmzWHMRM3sHDbHUwXNtDXmcyVM3Q9gEZ/JVO+PpEPArUw4B/YQlEsvWgJ0VE9Z2I9GjuWbWPd3EbksNxtmb4nDGbfz3u63Q+6JDxq1/EeAFK0HXPMXmLDDkac2vXSDMCqVUMwW5KYMOPnLverapC8+asZflqQE848o8c2AVTU+3j8BT3A8PE/TOLU8el8PftHXjtUT6PLiFx7OmKNitlgoKn/ZIoP+Jl+2nCe7D+IS1/KwW+NZtDVy1DkILISQlGCKEoQWQ4iyyHMcy5A9P0B6cRrUBUFTVPQVJnndh/msvwQ4xM8hCQ71Sf16dy4yHxr4/f5OKwC/U+28HhMdCutuEVnQQ4E2ba8jPg+u6hLDHNm/PCI/oKKqqmoqFTm7WbDrgoyxw6nPtZL+iVDaOE8aKqGpARRtu+n/EgNI4cdobi4ksrKytamuEwJjDrxbPZurKAhoDJ+TAqzDxQCMNRkxqPU0ShDEzYwSqhemT+KjZRRQJ+E3oieavpLDsyR3C6PFoPXZOE+rZxqayID7HqMzobPP8QcCjI1vIso9QhpYjWH6MUG9Lwl9pAPFTuJTV5O3b8cmhpZl57KlqRS/jy/nH2CkRPGa8SGJGq1WVytraTK6CImEEV/y99xry9C8e3EMiwJRQ3irgjR1HQQtX47+fEjcQ4cgKZpLPHJhIwmRsdFAxrFvmaKAnCB/TDOsm2ElSzIDLbSwNE0fmqOIr3ewKgGBUEQMAkWTJHw9rFuuG9fAK9BQBbBV7oB3+jxDAgLZCVn6xMDNOr8jbhdqUiKisfowhHWDRwRjc01bnwOkVnbvGQmO5AkIfKIaDSUCYTc4IzLxOyIbtXXIPIctGgG6R5ANcKE19Bo+VuN7Gt/XOfv+jJ1F/si/7ff1/7vkL+cuIwRvwvD43+K48bHcXSAZfBgnKefRmLdYdKao8lLSmWHNJg9uVnMGJjJsk2fsvkUK2IoSOCLv7aKP+X8Og2APZX7GHHSqYCd2FQnmnqY/J02dh/+Gp+zCCKGB4rCw489hiRJBBubePuZp8FRx80vXNqtq7Z662b2VhQjCWAyd73Q0HfmySya+zMFi98l59zbO+wTRCOaqiAau1/f11RdYjnKksAlEz5jxcpcYtRSFFVGEg1EW5P5ctZbFNXkcd+2V/GZmvl60/fceOIV/6Pr3PITW5UVuyl0TLekIIDWvfEBUGNt/E0N0nqQctdVI7WIoFfPkBWVk19YBYBBgynDkvEUl/HAQRGI5+TiDVSUjUaISkMBrPkCfaQYKt6sYUHqQvpKGoJowGzrfoavBgRCpjgsWcM7bL9iwyLiamfpX0ww8qQxGAxdq7vuXCGg2gxcdLrOivjkoV9x17UPUrWTTSxj6c2YGRPB7ISjErgdrnmDysrF3DT9Fmypvbs8zxr5Y8qPfEP/867h4CNPEm3QmHD2JSQO7kN0r1REScLfHGTnjlpOuWYQ+wJ9ueD51ezyBwBHm1tJ1jCIMo9PnQVMa62/pqKMT597gkB8CgMDIerjUvA0NmMVNAojGaCza8sxeN2Yh0xmSvhdAHpTTD6ZTGQjSvHHJO/R6b910XGoLhjdZyv9Ur7kh81TKRXP4KfahzC4REzSL1wzI4fw8mRCIZWkwdPQ5m/F0ieX+LPaJgxNhw9TcsaZGB+7ml4X6zo0Xy9egwm441R9eW956RbuOmTg9CFW+sR3rQS8ccsvPNlsZW6BQKOs4LWIxG9YhYBAbGo6M4t9RBWXEy7bgrlPDlmP6wnVKp5+F7kuA1NmiNhLzmf83lIUQeWXPpOYtc3N642TENFQVYj1qXx89wmdzr1rhcCyd35g6hWXkTtqQJft+0+hYMdWvnv2UU689qL/dFP+KRw3Po6jAwRBIOqv99E8/0QIQ4LuCOHJ8+HJnyLhkSMgqclK2Luh1W2fE+kMqzaHIDIOSwYDUy5K4fC+KnbVFQFw1szpDJ1wAoZ2gajmaBcTRo1i0f797P5iDkMvu7TLtvmqqgCYOLZrWimA2e5AQMNdW9lpnypICIR7/P2qqiErHlYWLqak9FPS0HNkXPDzkzwz9o8MiE5lYPJkBiZPZu3+aub7v6Qp0NRjnV1C6Bww2E2RHqGJIoL6b8j/gtBjWzRNiUjXHzsgr7DaizvyXDhEEafdxLb3lgIpPB2UmZw0CtHSjWHR6CLZLOJWyo/ZXqGL9uZMu5KG/aWIqhFNUJCk355SvMXwyBmRgKZqhAIByg54yGl4B16IqEY+VAnGtkDT5kZdD0NWuvdgVR3R1Xo95dU0eCoZ2Gcy/c/pKA3f3uC2WYw8e/Ewzv5IV92cneXBOTyB9w8WsMHaeTll+fdz0SrLMFeWMRDwVpTTZ+K5DP/bAwD4LU4MYT/5CVHs0vaTkx5Lb6euoRNv2sgeSznfO2M5315CgjeDquh8djaP4rTyAq5M+Rqu6vggntk8iaxZJ1O6cg3BOh81xY36bzgqMaHq1+ndgqXteoVRybO42FS5ixizEyVyD0Wh++dqpNXHz24HJ1zXRoB9fN0rmIeN4YE/XwDA5lfncGRrOYJVY8Mt9+hUXU+ISv98omuSsO1cyfixs5jbP4WKWi8fx6tEpxgIBxXC5fWYMrqezDRWVgMQldD1cuR/ElsWziMppw9pAwb9p5vyT+G48XEcnWBzxTEqejRbG7e0bjvDPIGRhgwQRE6cciUxCUfFKdwAb37wNezs2NkPnTmKfieE2PWcTuUdOXlql+fMGjIE9u+nsLiI7pLez/v8RwQpmbTxEzvtc2/fRt7S91m9vYicJIkBF97VuQLBgHCMRG2aqhIKFaPmv0oaUCb0YodP5XDtd1z040p2XdZG81vdtBxMcPspN/ZYZ1doGWx69HxEpMJ7bO9v8HzEeS0I5t/SefZ0MhUEPfXesbCjsL7170ZNpb4xQGW/XKj04jBHIbbrdjzmED57iGZXAMWkIkUZSdtVS8yxWbKd5a0BZ0ZfnM/0ZeXXe+mzrf6YAY/tdwsCJGZHceofh+AJeZgwZwJMgLeBv+Dgomaof/4LJJusHycKlO3bC0A40DnTcQssDn1J7ue330QSDfSd2YXxfJQg1bB+8Sy/NJenZxfzqpZJ0sHtZKZFs0np3GVfeOOfeWHLBkyeZjRzHxyBJi65/mz2/+0BVIuG59Z61CgN1+ZozE03sa7mRcr9UezMdfODy0OlIZa7C7NYGbuLZnMtZrOTUYM/YFljry4tYM/uLbz65Tucl3UHroAN5bMjABzyh2hvUipePdZCsLT1CUcs+nN41n4VaIIIwwf1GDf8qFutO+DaNhbV7qUskE+GayBEAoZxaOCHxlAVjaEqcnbE8n7zSdzSoJN3LWlGUDQCRR4C3gNMKn6K57/wEltbQvK8xcQMyObAr6sxmBNJyOg5Vud/G9WF+RTv3sHpt937XyMqdjSOGx/H0QkG0cDssz9CVmUW5i/k470f81PzVs6bdgNjksd0e5ym0i6gsQ3PPvcMAEIPs+Z3v/gCDAYmX9rZ61G0o4KFb+/H5NTTjy/+rprrj+q/5zx2P26LmcGuKqZc/Cim6M5qlRoiwjEGar9qo0HIZOTwZbikIDOi+nOlIDD1hxupb1zPewd+5oZ+J3LvY3+nsVcNyaFMTIZ/Ispc0AdPVQ0TDvnRNBVNVfX/NQVNVVHkMEZBJtxcBJGYBn2dWQFNRlMVQppIvWrB5GvGZrYjdKGrIqjab3Oj9ABNU/TMolrXS1blh0pZ+81m4tOc9M9p66ijNQGLWUJLMwNeDkaVYIvTr5cpyc7Uc87sVFdeQQyBqBSG99iio+Uj/zm01JC/oxo93Y9+nezGjuo126QzmRUzBc2jEmqKRtN0tlCSZTwHWYzJFt/tOZxx+rPo8TbQP3ciOdPHd/41XdyfjxQzi85seY4nku6vINRFqnhJkjjz0edZeu9NQAWWmFqWr+iN8EAUgqsZtcXuPKWcrJpXqd9vIjTFg7zrJE4oSWFx+mKu1tZwkvt29pjLmHXn3Yx/ewR9/XW81S8JWVUJKQqyqscvzPvmAGE1yM/ln3Jiatty4+qaKkaqKqYIe0sN6J4P0WrlWBACFbRoo4CureIvzMOQkohIZ7NYQOhw+xvqdE/ZH159oUO5sN9PrTfIF3++nFCyiTPun8AtD/zIhJxY5tw4gYaGekY8vx6tNo1SrueySXBK4QZuP/dUNtzxBM01exgy88rf1QCvaRrL3n0NZ3wCfcdP+k8355/GcbbLcRwTISXEjctuZGvVVoYnDOf0nNM5JfsUoi3RHcr97bYfsIac/Pntji7lrz+bx77DO9vqU02okaAuISIwZCFMVGMTY9dtQjGI+iAQieguSz6fujjdtWgwNhMOOREED3rIqo4l5kYIH2Jm/S+k25roNXQE6RNOJWHkSYhGfbDzPnwOBqGGsuCznX6jBBQEA+wNGBga9Q1Doha07tMiA52ohAAj6xjNHvpSL0pYZDsibQOyZPKQmLuWV4M6E0dSDS3hh2gRg6PFQDPKZs5fnYMl4KMr9HXWcGZ6Xg93BqaMns1Bu66fIWoKDsWPQw3gUIPYtTAWVM4Q3yXVqHDqzGXd1vPzykEIWoBqIQNFkTHUBHAZnRSsvA9RFIjOrKQuP41hs2DSOZ2pkIvfWkr+zrZ4iL+5/GgC5EpujHKARsVAhSGGvvGfk2YoaZdiJsJ3aAmuEwQe8JSQLQfxmlParn9EtrrluIRAIQXihZQ4ru38YwQBmydMmk/jjbo5iLTZXjoNVt+QHz2SSklkiKGBxJABTRMwCyJZxigGkkO1Wkaa4XOazFsZzCC0YABvoZ/GiqzWU5WrITbHyqRFi0gGjd3+eJoUM9G2tmth9tZhDuo6FMMbJLJol/ww0q5CSx8OJk/lxDNiEQ16rpolYZUn7BLnuxWG2Sp4RErHKIcZI5v05H9aay3IIT8nzHkKAEtsgP4Xds/6EmQzmiHIwQMTqKrKZXBwC319dcRa9YE77dlJTHx3BDmldkYejO6qhta/pjoOIoyfQNzGqVRPq2Ps5fe27vv6hmtp9qvUJ8WRlTkMURB4MSOV4ug2/8g72lUUkc2s/JMwGmMirBCNeYcW8VHuLs7el8Sg/rEkZm2l2HFh29m3rMNoMuEODqXGncQeVwK/9B/FCXs3MLT4IGmiBoKIzW/EaXNw8MgGMCWQn3YJPxImymLA4q2lWmr7fb2iCqkLxNIciuKV8sc5EkwkPnsMVz73yO/K+Fj39WdsmPslo04/m2lX3vCfbk4HHGe7HMe/FSbJxHsnv8eywmUszF/Ic5ue4+WtL3PD0BtwFNayYvOXCFaRAfLTXR7/h8vPpaBoEt+8tgBNkLFpBrzhRkyDM/SXWtOIKzxIUsjMuuEn0GSXGB1lQ9M0FFWj0ae7Ty98fgJKTR2rvtpGfUlHdkmZyYJiSGfi6ByKiytYsyEfZf1bmKXXyUq20GvYCBIVD1GSQqh3dKc2OvKbyDDXovQJoST2YrNyBR6vB7PJiMvXyLYKB3XE6teDINlRdVhdo0iUUlsj1oPhRgoqCiCYATTQz5zJeNvprboPgtCmH1EeOMwizyKyTokl2zZSX/OO0OyESCr5mMLvcFeY+LLmHPoOySE710w4bCI+yR9JoCZxsEk3PN50VOKWw3hkRf8oKl4VAqpGs9GFJPUc6+JVBVRVRBbciHUBzCGJkNqIpphRFAi6LcRkVJE9qPOSF4C7rgmI4tLHx/PVEz8zOmilytSExagR9HtxyjJSfDWpYkObTkOEvtxKQ4z8vT04lJBUT7TVFaEmt4ivt0Bjd9BCnqUv0U5jhBSh0tC0FVEwYDLFke9KZlGyiEtxQYTmqbZkCo2c+6DmolqxUKTEcpm9BJusIose8tRaBhhzSdAyyJG3oMrxILkxsgdDokhzc2t6NmIay0mr92FLjEIwGvD6TdjtXhzmJqwGP/WBGBrMDswaDHD7yYiKQUTsNJU31haipcxg2Y8d44eypjuZm2hkbkTtNdrtxm6Ka80LqEVW5mSDiR0DxxBVVIM9xofdHYNoEEFoJTLT5AlS47fwTcbVnKd+xZDoIyQkFlD4dTRZSX9ir3cXsVMySBcEDBYZV1aIMcM6e2kA1OIakowStv5TqDo4D//aTaSd/efW/Uqzn4lx1wDws3cpdXV1YBToZ7ciGO0U2S2kKfuxKGFGu8OYC3uj2dqM8LxIBuQfBlaREl9EImDzro8YouDIacJq8iJWQ2XNZPL76Ndn3aDxrBs0nit/eJ+UxkYMqo3apnpspmisgpGx7sMsicrEH5Rpbmd4ANREpTDSqS81N5qNkAcB3xYObP2G/qP/0OV1+E8gf9tmACZc8N+RvbY7HDc+juM3wSgaOS3nNE7LOY06fx3v7nqX17e/jqIp0BuGHwlT51pDcsNUvj7/JQSTCSkmpk0bQ9W5A1FyDX7VwrCCX8m57CT6jB3S4TxXLN/Hz1qQZ04c0brt218KqZqTj6xAam463qRaKKnHPCGea68YjCiK7H/pGxZXO7ireiyCRYBMDTkUQkAj01PCmEUbAQt9XCJnPdk5qqTuuY8xh0Vm/vlqAB577DFonaHqFvzgKA99+/Uja/QpuJI6xrwoSphvvnkcsQpOPOkuXl12NRcPnMoFQ2/u8nquK5jLotWLGDblPIakndxlmYZF23mpeiYkQ2i7mz279Sj+IdPSmXKxLpSWvGw1WZqb88ac3vWNAz5atwRBcXe7HyCACZ8UzzUzVvH47efiqAwz8rZrsWyrI+CNIz7Rxem3nNrpuJ0/b2PDD4XIYX3ZISYpmhtfO4/rwgpGsz77/+66K2j2NHP1mz8AXcTiHIW37r+fvUYjl9/xVLdl3n7qGWIHDebiM/QgxD21e7jvxzda928oLKH/4GUcufIRTJau3f7LH/yCQaYwR0JWfhXT+OEvp/HtS7OpCtXT/4ExCIoGz8hoAy+lYeFCkrIgbMkl57u2pHBNj5yD4etC+n38FmLqQHrt3s7OvFuJimrGZmwTBpdViVHZC4jP7ZrRYfjTn4hZey9pH32MqqioKiiyxgxFo9EhIkqw49OtNGjZZBubkWWVASMT6DcgFhQN05gkbvOu4A3t7/xF/CNXn/1hp3Ps3L2Tsz8vJZAZy4fSTdyY+DrV31lZnjWTypTdVCTMxey38N4nz+LTIDEK+mYG2mlP6B8BEXonIwi6XkeKfxw15lXs2FhEQtQ6zAKYQyotaiIZtmR6DZ9Fzuh6bv70XEi5HNJPgj6X4F43laaVR4i7ZhDWfrHsOVRL6b5aztJ607v0e4JCiKRQDfRewR+mrdDPCSxaNBrwEgza8Zss5HoaKIlN4gLVx7eijU/Ovp5NhQriAd2gqfDls7rqG/o4N3BXwysAxBoF7prlQGwIobpMzLCt5Ap1Lb6QgyFn/x1PRQFrPvucH1/8hO3D5jLruseJTerf7TP5v4Gm6kqqC44w66Y7MNv+++i17XHc+DiO/zHirHE8OO5Bbh95O4cObSL4wfPkVuwkMPQQW9UcPHUmUAS0VgKAboIkieXMvHsyqlmg+rQHKH7HRp+xr7bWe/Wq/awN+NHMHWNDxIjUdljWg0VVUZfXvvaKIa1r9JedOBz30l0oqq1Ni0E1kVevsCV6JDXROcgBH0OUWs7q6kcJtFP8BIvFQiDQFgR3xuBoRl/wWLfXZOnS18jLMzByZBzR0Xq3q/YQ3Kq0xJ4I3dN+o3avBHIASHaOpzKSG87maosxyZVriRd69mqEZS9x8gHmrLuw2zI2zUOzpndmmlkkaIVxI09m9ACNT/6ymcI9ZppqG3HFR7ces3XxZjb84Ab0bQnp+mAriiJiu3t42BmDPzWL7558MrKlzZvRYdU34tqusljwH2M1WEDr4ArvF9OPAbED2F+/HwC7phEWDMfM1eGQVB6blc1flhRzxvMLmSHXExYDPPnUkwiawEOEaAoEiH7gNeTZ07AaD+JfNRfrtPP19sf2Aw4gOPSlhMFDRuAvrMRm6MWgGcsorq1k/5J7MKSux2bu/nkQbTaMso+4MYM7bG8vB7bznQqcgoZXkQmENTasq8Tw+l3YHAkYxlzJLbFbAXhGfQfoGPsAEFb1a7G08QXclr3YVJXtkzM4zbmCDQGNbE80sgAyMMnnZ5zSyF7Pl53qORrGOoGfpl3A+zMvhpafKIFjhsaQRoWrd8QQkxCG0k0Q9sKmd/TPIw20kFwCAZm1y48wYFk50YDXAH21mQhAKHEdlayIxB3p74sghgkGhnP1VXMBeG7DNlb64c6Rg/h2h77k9L5UzR+MDqLDEFZ14bYJ8UXs0ElzNIc1/liuoiUf5Kppp5MTdR9wX9sPyxxHv9EXsG7e39i2YDUf33MXQ04ZyrQ/PIbB2DV9+/82Dm1aj8Foot9/caxHC44bH8fxT8NmtDFs4DR4aRrMvR72zSdlciZ5838k+dpTibn35S6P0zSNclEidd0yti9cwYgzZjA7r5wlWhCDBIOVjgNyrU9nEix8ZCO+JBO2qhAiQqvhATBhWB8mDOssKPXjqi189MtBFM1EoeAkT+w6al04SsPi3nvvxe12c+Sn91mwz8Ow06/r8VpUVzcTFeXhrLMeo8mv9249GR9axDKTejA+Amn9ePTQy4RvKEWIt+L3hnHGWjoMuhIayjGitg74fIwR/Rh9u7st41dVDoZ0g0hzBzHkJGKzOsAK0YmNNFZH8/VTP3PDKzq10d/sZceyYiCG3sNDjD17DLEpXdNnfdH6clWRx9Py42mJd2iL5mjZDthsNB9rjV3TaFbarq9RMvL1mV8jqzIG0cALq9bqKrI9GB+Fmotyv8pX04ZhNhm5d/5h9ogZnO8I0yz5SYiOx1ChELRJmPsNI3zVjwhfnoq68u8QMT5UVUIQNQRJ70oDlZtptqnEGvVA0cz4ZLTkYRxmPYKlhwFLENia2JcPH/+cZn+IooCAS1SJMug5UiQR4gUT8Woso67KYN37NQCsHXEfkhwgphmamq9hkescFg3ohWHhOhKt0ZhFkeTDPpL8Gh63hxP8Biq3Dycq5mQaZImGoJHyGA+WyJKUkYhBWLWb3o7N9L70RzRN0YOcWwKe0UBVWrdrwxR+Td6MUZVZ3jeFoKISVFXyy6u4zWjiiuheSHIQJt2iG9slGyF5CIgie3x+0gHvnAO0qGgcnJzEjNN1z15jo5/y2esj11pGFE2Ry6VhMLUlHtRkBRD59ddNJIt2Ki023s1IQfJ6uK5II9MxgO31yxEFcAZLcJszkIINXPzGg4QumU7K+GkEQiUIhohUvxT5iAYmnXsPI2ZeydIP/srO+bs5tO58pl55BQPHX9zzM/p/AcV7dpLafyDGnp6l/xIcNz6O49+DaQ8CAsKR5YgGDf+hEmK6KSoIAvX3P4nptWfZtWEHB/sN4oEKnU//UHoSNw3umM306Zoaxgyx0veAl7SqNkpjUUMNWTGdWS0tKGn2c++WJnx+F5LNgCLIxHaXvVRo/QfQGQTR0dGRNXMNo7VnBVNFkXU2CCBGDIqejI+WfUIPxkcoLh1L/hZM6fq5jZbOr6uIdpSse2dsDWeyNuxk4/lfdFtmyMdDMEfiQgwOG8qh6tZ95z9wOh/ctY72gQqz738TVRuFM7aekadO7tbwAIg1GQiEgtz5/PM9trMFTz31FHZ7V7mSO2K/pzM90xBJ8NcimCb2kDAOIBRhYJ07cSDvL97HYdlMdno8jhEpJCYnwRuASR/wDL1HEfYbEGxtBo0WlhEkPQJDDTSxc/sVGEVIH/lIa5lWWnUPz8M+Qwx/nXgjqXX1RKMSK6nISNSGBWRA0QS8RhcO2US/gbmsEcoRNf1ZVgwWNEFACOzF3jCQWdu9/OOsGAQlSGxzkBu3lXIk1sHcHAfKiDgGVhVw4qF+2APRWH0KawN6MKwQiagQ0EAYxA9BkXutbfdVCQT47J7FeGUXM6fV0++CsxEMehsMlv3EhZrpmzG6tXyCQYIjtSgCoKq6Z2vCzfongsYoE+lAnRGCZokRf5lAertJhdNh4pDTiAOo9vtYs+1TBLUWlxDC7S5sK1dSCEm53Gvr2B+4NnzCV4E2zZhFKwcxvO4fhExR2H1VaIBx9g8Uzv6h23vTgoGCRprNzD5fAotf/oy91m84/dnXsaX879BwFVmmdP9exp37+4k/+Vdw3Pg4jn8P4nrD+e+BphEf/CvVH83D/uOPRJ12WqdI8apAkM8LDpM6fgqeYCOHF/8IQ0YyVpY6GR5hj4deDQXc0/wWo+17eVJ4mHq5P2tMbi7XTJRV1BATZae08ACfL/uV0bmpnHnGuYTCChd8uAxfrT74yH4ZATjoFLllwS6dqalHf+r70/ogan6als6nIGBnQlEBDjVMnRuKwhlc/fiHDAkcxqn5QRA46crr6BUR9/npp5cpKZEYNEjvqJWIZPpLO75m6dZIAJvBSIMjGoPZDGj4Ix2iZ97lNBqidMGsFulkOUhpokZCtRdJ1eD5bNA0GhUzmwPpPKVcQYxRRtUEtg4ciJJgJfunbZhUATNgRcAqCthFEYckUR8MYT62VipBRXdN24o7sm/WfrkOgFAgjuUfrUAQJVRN9zK5h8p8v3kN2uaOdXlFiRpbFFFGA/tjkgmLIo+v3UxdmYfkGg8DY/QBXdWgTJZRUto8OglKJelNZRR+U9dtWyco+6hWs7j4l/1Y7UasNgMSApIgIAqwraqZyeX72b3i27aD2j+GgkCvQDYBm5NHPv8FUYC9YT02ZIP1ZQbUHKKsBqLihtF/8xtsdIeJajjMAKtM4QGFIw88iyYK2PYU0Zx5FotvfosBjh9wRSvEWLMpOfIGgqS7LBqrt2CKFajbsJJm0066wnK5Fxjh3KH9MRmkdmygyP/5K6gKOIiuaGLvrY8xweJEEAQ0RUPVwGgyIJgFyssW422IZ+vgy3nvjfcAaEiC+YExGA81Y8h3Y+grI2kCNkmjImYP/Qwe2pg3+kUyqwFiNA+8OSHyjojsKR2EV9bVNJevimX5qjVcmXwLTnMzYtK5aKnndPhNLckoSwSVXw/7sBgKOZo3W1xZzJKE70kcPZHk1AT2HFmDILSm9kMUREr7qQw7MpY9jc+RbPkF2VIPBnC59rBnzxI0TSOxfCfXH9rPhX0nUVVxCHXTUtxnK0hTHEgWAcOaaP4xdCjzrX15+/kHMMp+bGPHII3IQctw6J5PRUNTZVBVNEXRvTuqEvkuo6kqFkUhQZEpKKhkX6mPj269jhlnXsCAq7pgXf2bUXn4IOGAn8zB3Skh/XfhuPFxHP9eCAKxdz9BoDpE+d33UPPqq8RefgXR552LGJnN+m+4njs3b6E+yoUppHsymhYs48SMzrPnw6PH8Fbk70MkczF6h3ozUL74Meb0ncmXA2ciY0AknY8rDfyw+z32Nxup0hJIim5m5T1/wGaQ+G5rCa9X1LLfoHbIrwawJ8UORGbbJoh2l0JQxK86aNKs7PFZCLtLGKOUojTWs33VcnoNGERlZR6//tpErxyB8867HwCzaGakTaaizkwN9ZRZHQTMBpAbcUVeOUURCFrHYK3ejGgPRKTU9S53e18NRRJIqojEhYT9eqCfYOUkaSsnSVsp12L5Rp3KjsMZCE1heqVF4VM1/Gg0CRq1AoRFAUUEu6YihHsWV7MZbCRYE6iMqHECrF2/kEkTzmDUqSM4sGk7AHkbARQgClWuIDhvDv4uPC+rx53EphFTdPGXfnpQ6MoQkBhDuiFMaNeGdqU1lKK2Oq7XlpNJOereVd22NxuVQ550XlCHgDsIR8fTJqVTEJOAdPsrnY5tOVP8rD+xS41jzu7GyJxfHyx7uYpay+bVn4tX/olx+19GQiEUlggUNBG99zsETaMo5zxqUsdjBJoqbWQufx/NUEFIqWh9xmyADSPqGUmEta4VV5uNDiDMx4drWtsntPvAQFLUMKcfno29QRf1CpudSCEfYjvtml6R/6Nef5kq4S6S0A3JAVIV+5UkkpQmwqF48vrPp2qVh6c+6jqm4x+P3UEWlVCfHzGKVco9nQOOvSTgtJkQ0FCPmmQYjfqz/ooQRCwIQMHeTscbozdiSVkGhcugsMumAPAFMHfLtdjUs6nPXEpNvzmEwma+/bblOTJgVAXWrNIQ6AOuPrCqYx1n7+r4PeuTT7o/4TGQC4zav49FTz3MokXfcXDtL8x69iUs8d3rvfyrKN6zE7PNTlKv3P9r5/jfxL9kfDz33HM8+OCD3H777bzyyisd9mmaxmmnncaSJUuYN28e55xzzr9yquP4L4IgSaS+8DxRp55C848/UvXcc9S9/z5Zn32Ke+lS/Ju3IMXFccK6tayet4CEB++j4s4/s+WO2xl1wvgOnhKPBRztvOuF2YkYL74F66fvEVtWQq7JzYOGOfgwc/V9r/Pul9+wtkylTEtguHCI+8bZsBn0QeW8URmcR0eWyiOb85ld2wBIGIMKMarAOyNymDB9eIdyA+6bS8bAodxxy6P87ZKzW+MTGhp0D8bUKbNaZ3oGo4kr40K44i9l9PSHuWTZWlYaHDxrCXLNBJ2xsnXLPE5390IapRDVe1SHc5kX9sJnEwjYrVAfBlm/AA57FJvsp9O7aQOpah23G+YxNniAW6qfYOUfR9Adpn+iEexZWw0tEsCZkJWN6jIjNgXZ+MrbFFQd5Ipz7uKSG6JoKCggEPQTN2wEm37ewqH1c9EmXsC9t1/dqb5Fm/Iw+YIUTx/ZYfs5C3bSYEzgsccfoazGy/crCmFlFePuHcbo3hHj87GXKI/pT+rtG7ttr/vJVMZlpPDXr+rRBLj6hXE0zJlDoLyMcDDEohHj+XtcGoPy9ndbx0n33MMZ5nquevxxAF5/42qU/edjMegGcdbWNzhQYeLlvlvZ7fkLWigZTXUw4JpKFt+o6yusu+rxVk5USoUem5D85VfEDh6Kpqogy9R98gM1f3uE5NtGY87s2kX/2OvbeajUQ/pzXacOKHtgCVFD/ZQuPNK6zRh0U9bbRtqRzjoxDvy8hU59f1m4jHFGWGy8E02DCUdeo5JJWBODdJffWRQNaMmj4Ma2jMonh8OsfvFzGuoFLBaF2HiJ+Bt+BLuDpp+/wataaKgtQtY0Xly5lQ1hKw+vseCRwDHCzqkzhrW+Ny1aK8tLzPyjcB5X9n+ESb1G6MJ7kQRtKrqo2cYdi/msejYlQzUydqjEFs+ibGACA3NHMWSwAxDYtWodR9b15qI/ZRGWFea9r2cpdkUHGGd+hnX2K/Hm56JpMiq6A+ZfReyAgVz66TdsfPEZNm75ldl/uopTrruZ7FO7Z579KyjZt5u0AYMQuxAS/G/EP218bN68mXfeeYehQ7t2Ab3yyiu/K2GW4/jfhSCKOGfOxDlzJgmlZRRfdy2Fl16KUlMLgBQdjRoIMPmcM9iMhv3117Fffy07jUYOn342pzz2V+wmI8uu9GNqFBmRfTXiu3MIp1vp1VSKVlYCwIXvvIT/paF4Yodjj3Jxx/XXcvq+7WjuSnKXPMZqubOgWAtO+XwTO1JNOBB4IC6OPw5KQ5J+Q7ckQPWh7Sz94CnK/E2AnT17n6XkRwvxr+1Gm56F0yjBTJ2ecmN6Aisr/bxd3sA1kSpMMZnghpDY8RUsX3cLvkhMQU1qPCVJIhOTH4W1ryA1FjHgpMtxDPkEt6cZ899zmSDtw6jo53njTysAyA7v4+RnLsSYpIslaC0Bnr8BksHIve/OpcnfyJuP3UzVnOU8vWgVlqZ2npP5ekZh0ZiLYV8Cc1cXcf6UrA71CILQmrej08WLbH7+3e30KwmhiBDn7OgRSG3oWVxNA/Z4/Nzy9gw0TePwtOnIkdw/IoAkIUxPY88JgyHJgpSRRNptjxPVuy0mQdM6Kot63LGYpAC75z/Nn545HffIMNoDOwCBPgOX8MM5PzDpqW84kJ/M8L/+wC0npJBSvgaLVSC7aAmWiLBc0ZtvEPvmOzrTxmRCaFHA7WHlS2nqKM+uaRreDRUEi5tRPWE07DTts/POtTHc/0sp2zx2cqro0vCQ7Ap5X6XS+4wqTA6Fm9Wv2OG9lVLzFNKNq6mMiKD7he7z3giCnueoQ71GI9P/cnXnttdWctEtjzA0qzcDHojQoxN64/SpQCMORYAtKrXjQ4wdnNTh2HQ5FgqhtyOdCYldz+gDRw7xWTUMPWkYSsZu5AVmZoy4DLOrzctQFF2IqBlJGK7XYfu6Bl9ziKZGC0u1xznp2nSWHVxC0L2MbdnJ9J90Mvs/+wRBEvXBXJQQRRFB0vVzEAVESUQQpYimjq6/I0iR75GPKIr0nn4i0SlprJz/Dd999CbDflnBtCefRTL+E8rH3UAOhag4mMekS678t9X5n8Y/ZXx4PB4uu+wy3nvvPZ56qjMXf8eOHbz00kts2bKFlP+lYJzj+P3ClJ5G1iefUP23l2hetgwCAUJHjnBg+AgEs5nYhATSJ06gOOZ0GguLGfT9t5R8/y3hWYP4S0wDiLC0uYnMRnTxrPnzsQEpc7/lo4dWcnOyl1jPOhp2rKdgz4+MPPwaAF7JwtZgPNO7aJM/pLAjRh/kXx6QyZnZPbtLdVaGHpchoRIIKxwsrSMkgctViSAcQa3VXydhZRFOJNyZurth+oB+ZB/8ucPwbzCYARlZbqPJKv5a9gcXAzDUdQ0+fyFHAivQRl3D9nmvMsgmYFx0GRU/j8B30hPkCnr9otaRaluhJFN+3/1kfTw7suW3yasL7VroskZz+yPv8NWC1ynbug1jnYesOjdPXxrAKIucKJ7GvVfez0vPbMGzuAiOMj72evxdn6N9MxSNw8lGHr1vHNG2to76sCMHX+KQbnP8tMARMRQFQSD6gguofUPX+Sjs60I6eTCENQwzBqAW18DSfGr7fErULW3Gh4qGGGmQqqpMHn022+YGiOklY7E5cYf1HDWp9lTWencwYc4EpHQzOQ0jCPlm8dQvNTwWlcnwvXPw2234DUaCI1IY9fzfjr6wx4Q5y4l/T1uMS8O8w/g2dU6OuDYhwJTrDAzwNFOaYia3vDfR1YNRaivRQiEO7cknLbGBj9NuYXfSLgpit7KlqJRxjpd5o3IeaaaZ3EQNK5J9jKzYBnQ9Sxda0rYfBf+q7/AsWYDS2Ixnx0Eki0i4WX/+Bvwf9s46TI4qbfu/qmrvHnfJSJJJZuLuCRFCAgGCu8Pii7OwwC7uvost7k4IxEM8IS4Tz1jG3Wfau+T7o3p6ZshM2H2/VxY293Ul3V3n1KlTMnWe85znue/SIt6LaccoaGxcvQyjrAJzQvt+8cEBxr3Y3fiQgrm2stqza071yHyy7yOwg9rmC23/ZfCu1ymiaQFa6ptQAjLzbk6n7FADe1YW4WzYxOKXCkN16yLs1O3/GXpP/vqvIfg85hbnEfWPNxh16x3/bU3XFOYjB/ykDhr665V/I/gvGR+33HIL8+bN4+STTz7G+HC73VxyySW8/vrrJCYm/mpbPp8Pn6/zoWpra/uvdOkE/s1hTEgg5fnnSAGUtja8R/KQa6pRWloIVFXT+uOPRDQ10VX+7MvkPQzx6DPZjHcXoyIipSYjFut5/LU7tqPROeiV/7yOAXXvsN0+DfPEmzjNF0c/rxF5XSEqemDeiLgwTh+SiNUkYVUh0cNxDY8l63dx95JSvKIFAb9O3S34GNo/jlHXPMi7f3uOhtYI+si3Muzhm1i5cQ59KsoA+DlmCOOC7WQiszY6EafHjcNqC+rByPi7GB8uX3no+77WDwCdQjtpbS7LjnjYdIs+Y02qyWPQ9/MolPpys3ofbkHPhrnupam0VzQS2LyG+PNeC7XVyK5fHQA1TTumjs0extUX/Rkugv2Dcrj8HglFElAlKwsM3/HT52sZIc1iYON43liSx6UzM4mw6kZEmsVEWS9iax1DWrzJgAbdDA8At2QF6fizRgHItHbO3OP+eCvR11zN3LfHk9yvHyOiHQj1GtmPfwPAoSHZOlFWt3PuVFP94NGVeGtNCEgMHJMGgCegexUGRedgjvVR7aymsKGQ8LhaPr14HuMeXcKSsBzGs4X4LxeQmtXdAOvW2a4nDnhbnZT/nEvaxBGYoxyowXWxpm/zcefWg6wiWA3EXJaN5lMxJtnwLPqB6c1jqQiDMy98hRzzseRppsdysMqxvHnSTDTxZEzu3fxc92ci3RLRkoezoh+mzDeCkf1tkDG+9wusqXgaSjnyxmVYrMFYKEHA88z6btW6mr2iUWP49o8QBIGRnp3E+o6y4vRV+NsTyKvJ5tlbnz/mMFKHDkwvmUDeFif77HockvsfRdjO1oesqg/W0vfOTin58txKfC2Lee/WnloRyZ5yCf3HDCehXzKCswlVlvUgUllBVVVQ9OBSVekMLlUVXWsJVdXLVA0tuE1TFJ1LSFGDas/6NdM0DVGSSJ9zbHzM/w/2rV6O2W4nLj3jv7Xd/0v8y8bHl19+ye7du9mxY0eP5XfeeSeTJk1i/vz5/1R7Tz/9NI8G11xP4D8DUng49nHdBeri774L986dKG3t/PDNGlYlLmJ3oo1FpLGnuAx5xkQMOWPop2mo83LgvQ8JPPs8jL6U/c5JDHVsZlj9MyCAacafeHUtqNmQHwYFSnuITyKsvI26En3KYzZGU+L1s/T971E0UDQoObAPT0w0YX2zUDRYdKgRrxjJFRky15yuU4vLboH6hVvZaHqeBtnK6CSJgTP09Lfb//hnJuzbzt6UH4kPLML/3SEQoLLBx9DmgVxQUcjclATq2ttIC0hUF2+ncpeulKuh0o+piIEKBE3G5D7I+/Yw4sQreHv2qZyHrjcjOvUX9kXtd9MghgEBbvxkJ3azAYfFSFjSaCJ21xJubeo2sJfXlOg073QsNwQ9BwgYVBWzz01j/eGQe6KD9tyv+Ln5HoEIWQWPgW/P+pz9R4/wQe77HIj7mqKIpcz94Q9MaTiP/jFnMCRlNKqcgAEb9cUteCxiaFbo01RQNVqKWzE6FVrMcLiyBU2RCaguDGYzZrcbS30Z/r3ruqR7/GIJQFVwupzsKKsMbdPQePLc5QB8V7iajEovpTtbqGyrp82aiDHfg3P9DpAkQKDEEUGaUkvDgXXYGysJd2hMPicLq72N5r3b8DTV0q9uA4cPePjDhEkUVeXzXtNBpgmJ1H+9kS9mZbBjaTFieCrC5j20ldd1UZ/pNObKyo+wcoqdMQWbSCz1k6baeP/TjyiV44n4cgFX/+EuhMIWBMC9U186EowiYTNSUZp8IIKvrB3BYuKO6suQG9toEd/EMqZDSr2Tnt5rTKXeuActOKgLxlQet6QxpiKZ4a5FEAdp5lyKTbMZNvt2WlpaEEURSdKXHTr++TQjmhogqW5TJ6GbqlERZPv1Wq0IQVkBQVMxaDK2eB8xpQtD98OrGZiyrZwawU3D2AcwGY+NVTAEU6EVtWfjw5rQZTqSaiZ25ChKVy1BbHV0qxebUUZjMYw7+1ZE0YAgSUiSEUGSSOyXTNqgLoZhfG8kAP+eUFWFol3bSOw/8FdTx39L+JeE5crLyxkzZgw//fRTKNZj+vTpjBgxgldeeYUff/yRu+++mz179uBw6A+HIAjHDTjtyfPRp0+fE8Jy/+HwK35Gf6oHYn5XVg3fRqP4jv3DWz+wDx6LgTtzfg5te9x6B+81j0MD8h6bg8Wk29h/fXMlb2fHH9OGeVWVTqXdCxyqm52Pz8di1gfyN8+aQyA8iqa+2UxN8jHrhs64ksS1uaB6iavQAxIlRSDOl8DE2om6pscvMNu0nvG+Dv9vV/USMAp+Fpoy+EuKSvvhp0mw1WFJkaiIyUTc2kzgn5w7nJn8HWsjep4sdMUfWlq5rbm11/KipXH423rmSWkIg5tv7eyPO+w0XFEX91i3X5Wb+VtrMahGSuLDWDjBxozNixh2ZDcA5/XZT7qj5Vf7u7V+KMvjTu613OTzcfb3C3l55AWsTB/XY51rpaX8xfhpj2UBj0jhD717b+1znkW0/nMDWUAI8GTEndz9oZ9AtMa6sOEsHXw1Z7j1Z2p2mAGbdHz3lM9RQXO/5bQmbOq1zopWA8vaTASM6ahSFBZfCT8cfhSjZkSkhWTLZQCUkcT7HJ8ky263c++99x6zXdM62WVffvxRVE3j7r8+0mMbO3Yf5vyvjwY5RLTQEx76NDZi6f8iGgYERMwqiJ0mMgLgEvUlvK/zHyFctaFpDkShljj7dQA8EhmFsr8fcS0WTKLuQQoJCXbtjNDluF2WIoUgzV3XJcFu34O/BaG37/q+HfQkoiAwes5css75Y6/X9l9B7dFCPv3zHVz48DOkDhry6zv8H+J/TFhu165d1NXVMWpUZwS7oihs2LCB1157jZtuuomioiKdnKkLzj33XKZOncq6deuOadNsNmM29x74dAL/mTBJJtbPXc7nzz7Cd5X1nDw+BsfwEfhqavAvW44qSuSnxOMKTuz/WH4ZEclhZPctJL61jbFeA9dPiQ0ZHgDTq1tJ29nGVf84i4e+W8aH8Xrmy30zVZTVO6kwGhDRSPR7uf7Rx5BEAUnUeSO6BiaKkoSj3UkTsKME8u+9lzSHg8QRYWS0L8elVAMwonEo/doGhPbzODw8c/czqKpKWVEVH33+HtLElzH8IrOmA6veX0XldhFSbics58/c2dDEReVO2qrsDOUdBCAl0kq7N8C+R+Yw7MNRKLIZVbGDYueFKW/S4gnQZ7HA7JaJhM1JCwqrBflEOr5pGqYN1zHML7F/9kN6WcecRFNRVZX8lnyGfb0NMiNpuvICfQkjOLtW2gykmPqQWns/FXH6dbK2L8XiLiK1ZTbJtRXYPU7Mko2kiQU4Iwr5ZIzusM+uGcPt7zcBCvb4/qSedzbr/v4ofUxeJl0RZJXtlKSlY/ioeOIpSpOSmXhLzwZO2eIf6PCJnDQrg8sHRGGQwtAUVU//VVWuWVFOiz2T2rlf0FLtx+EIw9KhRiuA1t4MP9zfrV3NYsF27pV4PvsH0pRwDDkZSG1tWEQDnap1HY4aDQGBw0cLSDoYyVmr9dm9sUlgdtM+do9aBu75DJlnw1doxFbrJva6oUFeCQ1NJfS9dWkxzphcWuO2YPX0IyVmOpHRacFjaWiqSnveAUrXLQWzRlv/U4hNXMUytwtjkIxMEDrjcJqMKUwaOwlV1ZcKfvm5Z88ePJ7e4na6j8ya2rvhnmY1MM1YhF+Tupge+pWJS45HFaIpqZmJOCCWnFYj6XU+EDQCJhFbWphu6NTtIKqtleQ+TYjWAIpai2I+jCviTAKeVta2FaKMbGBQSTi3pIwJPrvBZ7jbd0IikNC9jtaxbNJ587rV1VT9uxqqr++jqsHfaKiqfi+OlrdSvGvzf5vxUXZwHwaTmcSsnnWBfqv4l4yPWbNmsX9/9yidq6++muzsbO677z5iY2O54YYbupUPHTqUl19+mTPOOOP/v7cn8B+F6IQUrn/yVTZ/8A6Ov70FGzZjplPubWxbO8tnTEVtqiLDWUpSVDv2A+lkDV1DyuT9KM0zcbX3Q20NULM9D2ezD0GzYTAYePqC08lc/AUVlm3Mtp/GZ0aNEQEPZSYJMdyK1dS7e1MQBBL6pDJ5wgSO7N1Lk9PFDk3jjt0v4MmMC02vcmP2I2gGEjwJ2GU7VqeV+pZ64qPisVh1emRF6T0HVgwuVWw/bQsNL+7mT+JWLjI9yXuma5nma+Wlm2Zx9qcHQ47+8cmj2Vq9FdHoZEDUAOYN05VBflpdiUMOZ/r43vUg/Gv7ozlSGDr52JkuwAgg76Fs4sYNIueiO3usc9b9K/BvX0vxxddjslvwufykLlpE/JmXMSkpnbx16zGH76JZFvgOPV7BFbsLSGPY+LMZc86pRGUk89Gb4TSZE7HM7Z3S3nnvK/SfOoDRg3p+Ia9da6e6vZ26yAQuvvIyxB6YbbPX7cZgcZAw6jQSemhDba6n/hfbrFlZRI0ajecziEyPxT6kTw97doehUI9Rqr7oIjbv/Jw2Gzit4IxwQTPI8RrmZitqjQtL/8ge27CPiKdtzWokv4NJ81aGtiuyj6ovX6D1s2+Qin1MBIbaBcY+dxtwG8s/6JwoNsmxKNpilkk7qKQN2649uH0ejEYjDz74YLfj7dmzR4+F+BWIgoisKShyADGYGdIVgipwt9yfg+YKmtR2JgQGcNhQQYXYRGx1gPE3nMeCd3czsu/ZzMnIYt+P+SQfbGFPppUzztGDg30rv8K8+XrUa95FjEvu1v63P92Ny1nENclDedeay+jLX/hVPZ//aXxxw2ko8q/ktv8LKD+wl5TsQRh6Y2f+jeJfMj7CwsIYMqS728dutxMTExPa3lOQaVpaGpmZmcdsP4ET+DWYrDam33w7dZYwGp97HsFqJfmbr6hv8OO/6jzG5R5AFkXqYmOo+tlGwi0/4wSsOCHmPTZv/QhvQTZNhSfjDAwmTNCHE0EQuOGMS/C3zuPpF18EUSQtM5PyyjKddvM4EAUBVZYZOHcu0SdN4aNLbuXSdg3nmK9YcgR8gpezsnX11j2xe8iIOoPxfgPyAZm//e1vpMSnYAqm4alK7y94QQrm2JgEzDPCqF8ZzjmmN1lw3yWdfeFgaLb9zinvsKFiA33C+pAZ0eXvLRjw0t7YQF1JEenDRv2XXmRqQKCtsoEdHz+G6PEx/eqHMJk6gx6z+k0laeEqwh+bR0p2Pypqm/jqy+XYzHb6zZxIv5kT2by8lUDgOx5NdrOp3Ui/2niyT72Oky47HYMhmC0kCD1mWvwSx6MrL9h1CFKi4Q+39Gh4AOB3QWNF7wcI+tGj543HeTQWU/9TQZBoW6/gOO1l8r7OJ35BM040PH0cZJ2fjSO+U2lU8QfY/8xC4tyJtPkb0bYPoSXxQg4mbiLGlcz0Ij1OaMaY8RTm5/1qUky7loti6lwW87fVkX/zmUg7W9EG2Qh/4Wb2Ll6J9Uhn4LKk6Ub0miH7OWnoKfBFNWHR0fSJjKC8XK8XCARYtGhRtwliZHMzsfUN7BsyFE0UUUURTRTRBAFVFNnbP5uHrr8LJp2BKeDntVU7f9Hb4NkYTLwQHUm/fglM264H8CYGIkO1Dr29EtHnpabFyZLm3Qybn0lJgwelyzJoy+rNNP2QjGn5yUh2A4IkEHvjjTqh4ctL+KiPG3noCvoYDPozoQnsKW/BYpDYWdpEQNG4dsr/3vgjieJxJxX/ChRZpuLIIcaf1bso5G8VJxhOT+A3gfhrrsE+eAhlV16Jc+0CEqbMpOrWa4l+7T1cdhsGBLJc8Pbqe9impPGAfy3jji7CVCggyPn4YktI/NvXOFsNVGzbhub3U/XRR/hKy9AmT6Kv2cyk665l82OPBBcjjoXS3k7rokW0ihDu01+ke/K2ktlYixDeKWon0jnYZbpP5QytL0ejitictJmxDWOpDfJRACjHMT50zhEFRVGInzOSmK2HOOg24/b6sVmC600C3fo7LXXaMe10lL5981WhbdHJqVz2zCsYzR0CVccOfXJFOc3vr0f26vFb1sl34dv3FembvgBgrdXCnCv+gqvdzZJ7nyDiiE4dXrR5DynZ/QgEz03qMhOdNPdp4GnqKvZwemx/TJZjNXNE/gnjQxDgONcuPtpBDRCV0btnQl8UOc5xRBHLuJvwawMwD7Sj+SsxpVvxt4HgiiZOs1FqhPSAgKPcRctLu2gBKhLqGXH1bIo/+5lYtz4ZW175HpGnXsr0pLFcnnQGsf5k6jLbiUmx6x6uf2Ky7qKT+8RZsIeSm69CqPMT+dwfSTpT10vZs3x1V3FmVpy9HOezhxiQPJC21jaigObWFhrc7d2MvF27dlFQUBAKPG0LDyesrR3l/PPQZBlkGRQFQVGRFJkBQX4aixzgfNWFzWLSs0DUjiUJ/d/7koXyKDh9eCaN2w/SmmjFUOumRdOwxyhsyl3Bx30ug2WN5Az7ExUBkZe0tzF3GZpUs34NjYlxyE1N+CoDlD2gq2EnIUCdncED2hnj9YEgcNVlegZmgzWCvq1VrOkz+n/X+JCE404q/hXUHi0IUqoP/29p798J/9/GR09xHF3xL8SznsAJHBf28eOwz59N64sf0vrih4A+sC4OztgEVWWPJwkkeMo0gxcVB4Pkr3CbzLRZEil7/mmy9u/Fq/j4Ys58Vs08C9kYydWr/XgEL00PDSNgPINqoZqhHw3lZFd//pAwAv/QU0AQaF2yhB3bNtFqN2H2+dk+byIZjY1IiormKsDbtIVdibFsGzcDu+xgqH0YgrOdvwmvQgsIZoEbzvoj9Q11rFyrM0d6Kqtp2NWFUEvrXIcOlNUSJltoPFiCN8LGDTmJPL7bz3sfbeSUiUPwqAoeRSWgamwubCDSbiTGbibGZsJg6DKaCQKCBma7HZ9Ll71vqqrA094WMj72KkmE+Y1k68xbKA0N1L+5G1WNw55ej4CGomazddJwkgZOJ+bvX5PyzDesXLqOPrlVDAVKEzPIn3AKA4YmsG/dtzQ065znBuHYF3F8au+MrPqgePyXtyYIOoNoL7DEx6G6ndQdzINZE3quZLLrNNy9QDSZMCbmIBobkWLdRF00G1NSDBvXHCVzZSXb400MP7UfKTmxFBxtwvbOIQBSa+NoeCaXsCBd/+GkCrRijX7tAjgrGTlxCpbwMLLGdF/s+TVSxgTtQmrlb6le+g+aHnwVwgWSPnqV6BGnhOpUtVfSR+kM4O9YOhFEgaioKMBFeHgYYpgVVVVxu920t7cjSRJ+v78z9kMUIT2dkQ8/3Gt/4r5bzWy/k+cv7jmz0a+qvL9+H7HZiRjsurGcmhNLxB0ZoTqvX/196PsYu0xFi4nqQAGjWvpyuKCBnKxYjJl6Vk/i619hSknEn78PzdUCqkr9fVfhaTJiHH4R5OrCifft6i6geEHBWuB/z3MgSdJxJxX/CsoO7MNktZLQ9/dBqd4V/1K2y/8G/pVo2RP4z4OiBNjy9ThUZzsmMZrUhIt4d2cbsXX1zFqjM3zeNONuSiKS+OvWD5hY011PwjzmOj5IaeKduZ0voz9/04RBBU/6s+RazeyPKEUVj//yGFYRx2eBXcds38A41jCZn5LW0WbpLoyW0J7B2QfuREOjKW47quRj+O6jZOf3nIkihqdgn9n7yx9gKm29zt0F9CUi1yn6OvlAj4bZ085t+55mqFxNckglV+NJpdPlfpP5HQKtuuZHq0WjMZiu27cpwAGPQpGv89oIciM5R57CZfDz94sGs+iaT9GeTMYsBGgPmHi7UOeSSIpQQdNQVQ2PYscrxHZmFHTXNMPbXklcm4dBLUZEQSAgBGgwVGEUjDjkSCyqDXNzKflDhlE1bHyXBkDQICArNAu64VNUZCQvc3CwuEvIowCX1+ppnPG2SjSt+8DfQQI+2awHdVba6kM5GFLAQHwgkqNnJaNV57Lzyw9C+7n7T+DCEVOw7ZJoiWgi9eKxbPriR/JyF3drXzRE6kcIBtGmmdMYFzcHl/pLnqMOdloNV+Y6mgcsJPkW3bPmt5qQpc4AWQBbu4uSeHj+kggEBOLkOF6o0ON4Wo0eIgJWfjDtoCSsWpcD6HraQkd6NRibReIMMn98qHcl4tdvXENAAleWozP9QwxS1YkCqgCHvT5myjDRLxHe7sdvEvFbDGjBm19QvoUDkzcyIKqI5xoCOIVo4q138elOndOmKcqHVHwIcd2bFI+bhM9uQxPEED17vz0bMbU6ib5EIz5Qi09JpD5XpL1ToojkU8FiD4ZX9/TH0tMQGAwYRlAxSC5Uxdy14JjPrinWy+vSOOqMxqIZflGXTk2pYw/WY9+8AiT2SeeCF1/vacd/O/yPZbucwAn8X0OSjEy8YCsVFR9ytPjvtCfUc92Ii2g/uTNt8M21L7Jw5BWMrjuWolvwV5MakUhM8yr8Sj5Dyh2sHFBJWeQhIp0mWh3+Ht9Pd6f+gcSwZJqcjbxY+hpJsS3UjPwwVK5pGknLrmagHEHy6efj+GIItnQf/U5KQQ7IJGhJmAUL6ig9e8TdFMaOlTXEDUrBdtVVet+6DQQiSu5R+IVqvGIRaJmThsFgoGZlMVpQUO3B07Jp9ci0+2Sc3gAun4zLr+DxK3QkZmbXFjNg+fvkIdFqCefSzL2hds9mOUuYSbis0hZrwewuQgz0Y2u0kWS7/uItqfZS5pBJniOgonLoYAnRRf04NORFANJqV/P0um95WAiwdcCfSJt8HoY/30N8lImocCOCAHJTDWFigKbw4R2JCLqLHkAT0FQNQ4uCQ/XTbLVgNgvsC9+KLAIESAhYGGDOpjUiFi11CAmRcd1e2p56D6URdgqiB5JYsAs1uy8D7MHgYe0XQ0Zw9Ss2Vs+86WqYAPgVAZxQbKzDmxCg2ttOu7cazQwuyc2yvaPp7wmQ03F9r7qL0+bO0A2K86FDn3ngAB95uZ19dEQk4mztzl5apXg52BxGclZ2iGlWCy4MdTxf7WUJuD05yDHloJoI9O8fyuDowOHqQvb2hYHmTDRAlf200ko7HgwOB1XtlZRYKmnDSZwlrst16Zqpo1FnqaexvYJFt9+NFPREtbibiDIaMIgikiAxP/ISnIpGTYkbFciTBJpsUijrR9Q0JjXJxEVIiJKCTwCPCppbV5gWNOgbMQrT0dH8I8tMVIyRaED1BViaJBPlV+nvkXFGJqKmD0dpa8XS0qQP4EHvYEtYJFEDJeqMGi5JIrYOIgcIRA7ociMFQZdH6i3vNlS1h1xbDTTMqJoZTTOFyjrvjBDKwuowqAZFGDCKVhTCuvThF+0ec/xjrEA0VcWXl8eQCdP5PeKE8XECvzlIkpn09BtQVD8lJW/g9aXjuUom6sPOx3nJlM/o06YyughqwyOR7UOQ0+IYkxLDaykfIrbDdGkU/foko+BgKjmIDpFPXN/gUKz8dMkqFm9+gj7hGWSmTCA5qTNrYMlH72BzhJE47uxu/fIufpkIoZb4cTmEf1TLUFssE0f3TBLeXlFP7lInkdlW0s+Z2WOd6gIN5RfGh+TTGOg5QNu6RiL8GczDyAabxh+m9ev1ek1YlkuTqnDz8DRW6Rxc1HjD2ZJ+JoIooQoidc5mWoUUIvbmcCTPy71Xp9NiDcOgyRyZkoXD5ODlWxPnwQYAAQAASURBVFYRLriI360P1ia/iaLwZiRnOKIqMaJ6FisPfMCIjD684PqZ5PQHuf3zRd36UvnSlVjbDxH98F977e/h7Bzc1jjyRl5PszGR/X0i2NxHp50/xTSOiy9+nP33bSQu0UbWH7uL8t3xXS5fRgd/ZKZS00saM8Ab9yzFGiEy44Ge5dDb3U4+vms7sfPsXHjGXMYsfR5f/TcgRqD6LDgrxlLiddDcJ5XRtfWIG1ewdvFXGGJj0dQAgrcWc6KD+ko96Tc5XKaqzRAyPEyiBXOkAw3wutrZ37qFJvNgBuUk0ehppEA8SGxYJOdOuxqAbx5/iLLtcMbPub2e0/67biK6vo5Hr9bjcooLC1jw4J1knXoWZ16le/vu+kgXnBsd6MdZfedz1syrj2lnyptT6e+SkfLz0TSNepNGo1WgQQMjuq7xwL7gkASSjQasikpKVhQDr+tO//36jWuwZMWQfV3P/BStZW2sf2onz45NZcDcDAD2PrESTYIRf9aXkx5a9xPTk5vxR2URbrHicpv5OfliNEFnzhEEOOJsY2O4mbLJgzGZ/m+zQsKA3v8a/3m49+yh9OJLSJs959cr/wZxwvg4gd8sUlMuYd++j9G056lOTmQ0TaGyVoeAffY8nEOnUFr1Ck7bxURJNXxvrg7VKfGUUeor7xawGatFMsE3AoclnItmPtfjcVVNRRSOTcUVTroZ86Yb8b16Kap2LdJxSKO0gAyAZOg9pdcYJaM0Goi6qC/2ESlU3L8RNHDvb8Tvz6AucR95roFYlONLEnS4eoePGsOQz39g8WZdfXXi1M7U2zkbFiLWC/SJK8Zw2hb+lnUyToOZO0ok5m9dx3fjZxLRVoLfnMSBNv21oWHBKILfGMAUlKPv1zCCozG53GkqJ/r9IdyUPAOju40RjSb6VX5NClDtjWP5W1/q5EyigKfdReWRfXhaC+gzZA5DAZunngvfvIAtz3xHXXMOxuQ1BCQfWVH62rcEaL8QAfTICuscGtlegRyrl+81C7+K4yw6GyT9PDuov8eE29jUYOHA5bov6e1P1vE37R5+7vMuB1qbsH72AoIGQm05oCFoYKisRRAF4iMMnPP8J3z+4juU4iE8YOJsbTqaRaPPI9P44J1/UJ3XQF7jTvI2qSSbDJS5bLw24CXGZo4irc9wNE391YyYpqDg4j9uuhPRYApNqAuWLeTA4MkMGZsTqlugVvBU0ausrFhFuCmch858BodNX4ryxiZSmZbCrD89wXc/LaZx33I43ECfyRlMOONykvuOJ+9PSwgkKAy5+0wq7t+IvbCFQ6/uZtDt3ZWMleMQ+FX49Wyjew/ez/l/38f3k0T+5H0Us70zEPmawrfp27QVmraGtr0XNp4KS2qIsUY1GBjdJCMGZPg/Nj7+u+DeuRPRZsOSk/PrlX+DOGF8nMBvFiZTDOPHLWTx4k/Z0yaz9PbN7Lfpuip/iPXiSFnIkca+SAkxnDnrAMtyk6lyu1g9dDX+r/NQgPRfSJivffFLBO34r3hV00KaIN36M+sivE1VGA+9gcZVGH2HgZ6FoJSAPqCJkkjpFVfi3r4dgL6LfsScFQyClPQ65oyOtVN9/d9dnYHBUM2oO25h+PN/54j7V2KjupyOJEnMn3os34eAQGSSwq3nXgt08mtEGbdxTUE01+5czhM7XsSdlEjWO0/jqSmm6brH2DJY4pbvDiCrMl7Zy9v7ciEYZtMkCTxZuw6ACYqHd4CDLfHsb0mksrhnVtGG8kJcacPAZEEym5jy8MUkLPiZ+JW6IXjGlXr8ioSGZug8sf2tLmbvLgCTwNSAkQSTAt5/Il33OGXGoPGhqB2smUK3PVqWvoT7Ql2YrTUimouHT6b5U/28ok6bTPPSnxmwZilSsp5p8d4dq6i2mcDkx2MCfLDEtI4bmcZhs52Y6p8gawhea4Cnmsfz4LgXmVbrwb1+N1w2PBiEe/xn0xoxEE9rHppmIOALoKkyCBKCYGftO0Xkbijngpq5CKqf8++4jrsX3cpWYT8BTWPf+/MYFTMcSZCQ5QZ8hiieWLKaQPxGpgzZTt7hvhRvLkGV3+K8u8frRrsKO3edj+i4hning/BqF5qmIQdUvnpCf6abC4o4+FnPKsUNrgDmSD+3jdwBI+Gvzxj4+tR1zDLP6LwPmXOgYiXuG3dhKMrH9NPFfDW8P4Z+OZTdN4yfGs9lssGJI/JMhN+Rk8C9YwfWUaMQDL/PYfr3eVYn8B+DpKQUrr7mHlrfuJv0ytOZ1rqOtH3FxA3wkxjmpDp8G0X2ISTHzSY2pYTqAqhfXUYEuhHxX4GqyYg97CoIApYL7kZTbkO9ZSOtcu/iaFqQB0CQxJDhAdDw9jukPB/0uAT7t/jzr7A6fQxmGJJQjaqFY7D7+KQwn6+sQzD69ewGn1+mrd1Fa1s77U4XznYXTpcLsc1NW3wCi3f/pB9T72znd6AtYMSuNLL60C8UWYFLxDoWVc1gX584sqvqqDy9002/b5TCV3ufQxJEDKKBCTFpXHLeT5zzwzm0+9u5PvoCPqr7hoJAGJtyHkYQBPoAfYJBlJomcNRrZNf6n9FUP/j9ZLncxHg9NH2hL7XECDDOlMd2/zAqt1fhcVqxCwK+mlYqVuxBNEp4fBpYwK5onNHfwdsl7YxsP0r15vwujJYdF1//Hq0V0ehJ467XVjE0KRmrRyPdYUYyiIiSgBhMEZbloKEoiAiajydvvIMvTjmD2LlXkFHTToNSz30pMcTf9yd8eXm4d+ygbWMuXS+w2tJAfP5qBrTkI0aVgWbjUNhSBvXTibT8sgxqADV7CF/m6twpXxw4h3kHl7PXuILsy67WmUR7sD1UVeXToiPEmCJAOhVL1DxufKv7Up7P42fxh1up3usnQpxBQfwW5rxexsO7BUSTyNunQZ25nZXOzWio2AgjpcnMqkQjt7XuRfZKegyJxYZk0de1NEEDVaO1dTdM2k1r7tVk1Z2Es9yJZjfSWqczpDY7HazbeGy/O65P9vmdxJQN98vs27GG7WFHkPc5OGXYKaG4Jpa9i9ZSEbyFKoU7t/FDSRqwg8MzPYwqnxX6u/qtQ1MUPLt2E/OHP/xfd+V/DCeyXU7gd4FHHnkEAHNTK+eZT+ewt51Phz5IQuNMYnx65LxRBk2SmDV4J7KlETQJQRCxNGURVTEbUTWRqV4BQJVJd9kLwUUZoet7X5XZbjEz02kPRrlroU+Cs8EP6vUMCANtYPnliKGhyQKKHMbI3FcQ5aJQAJ0gdmYgJIy+GUNkp+fELwQwa14EQUXTYGmShbbNrwAgCxIGrecXb8WMUXwx8JxfvYaXNC1gXtRnPZat2ziFyEONFKeYGJRWzTk51/OC+wtWtFUfU3ftuUv4ZMOHvF/3TehcwprimLinb6hOR3aAR7KyJKG7Aujdu77g5PLumUSyZGH3yDtxOvQwzvmR3V3rLgmmz3KEgv5GtR1k6Z6bj3u+n3A2RWTo+6tmMup6Vnk1jXDyhxvPZMbCq2ho3YUn7Ewy6vIZ1TiESK+ZS5QxRE2NJnzuSARB4MiIkWhePVhnwKoFOBd/Qe1bX6P4BJwJWUjhXgStHqFawewM0D5hDCp9SU08md1DI/juUC5lbW1Mat5KdKCF/umjsIfHsC3/ELm2PiRmDUAUQERDFGCjczvtsfmovjhuO6Jrt8TkgCB26o7oS1zgaVVoKYZKaz1fmMNYtvCe0Hnm3/AcslBPQdN+vGLEsRdCVUEUibOYuOX+Byi+/yskkx9f5lrkQBOKK5PI2nMIoOEa5WH9Gv0eDUirY/YDx+rIaKpK5b6XWHz4dUZbFTwWCdkr8UxVHNV2JwAXRl9EdqmHcxteCz0zqmahbdhiWhSV7757HIChV+cRXzafla6xVGk2JhsNLOkTQbLRz5DifKaVH0UkGFiral0EWvR/esyo0HHROo1zgdA2QQzS+wcze4SOur/Y3tmm8Is26bJdDP4OCgCKYmebooDc2ETT+++T/tmn2EZ3j2v6d8a/Mn6fMD5O4HeB+vp6Xn/9deau3MjyU/SllP1R+8mPzOfPBbeyxeFE1QRMYQm0DirkTHUx/TgJt1KE07Afa0t/kv1XkZGnz8J29Jv8iwj4znzQsQUbqJbiUOPmowkCAmLwUwhFwlevLqCpNRlVETBcFeSZ6KL7UdlUQeSKEqrsG0gfOFLnVkANJi+oaGgkyV4yxEuwSyu4M3kfhUYTi8TuA+oH6xYj+9twTD8Ps8UKhYUo27dhDgRIvvhCEqZNxfrVJUiSk8g7NoSyGjriXDp0OQo/PAWDUaPPFQu7tR/x6kh2KPez3zEBmnaxMn49mc4swu3NpDhi0fCCqCEIKnUBFzu8rbx6+WOkhOWwdOMXPHz0eTz+Pvhq5qP6Unq9f6+cHMvgrFQ0GR745ADJXifPXjO2SyaHhiqr+E0RIEl8/tANDB4xgyFnzyW/YA95udtoCARocLYiBlROM+5lqr2Qpv5jUNNPxpB6WnDw6LynH370Ec1qpzpqXM00MkZKjJ07EkXWUGWFhS/nYprWzB8uOZfVVQe546fOQfSCqlNQfGHEqxGc6h+JQW4i8ox+VN59HZpTHzwdfY04jwYIGxxN/OMvYRrUaeDUrF1D9b33IigKkcOvx5A4lDq7SJOrjILKZYi/yMt8L3YOdaYoIlS3/pwIAioCLqEztuVGtRybK61zWVDrPN+O75oGtRFHEIu2kt1cw8iKagRJpXruGcSN/ZKGaCPrNl/Z7dhRooASCNAmGbDLXqaNHkW/HaV41Z45VFa2BvAEu39Sv7UMuffxY+o0lnzN/oL7OennRgRAQeCvsVH8GOY4pq6oaXxY+ChxchQ6I5tEiU3gveHF5LAXozecw4WTWNneyXHiPTkZgnFXd3/yD07fvK7Hvv7bQhAYuDcX0dS7B/XfDSdSbU/gPw5xcXH0H5TNhtIV2DwB3FYjlzcZ+dxm4K6ZY0EQGVdVSqXdQaUwmLGOBM6acCMAm7fMxCMUUCI9ib3BhMkQzdjLl/Z6rIYHh9HgHcrQv7zYa52CT68gKj6PvnfdSOzEs44pz61ax+URH/HQyGs4fdidPbZx9PNzScrXlTtfj/4LhvHzkVIyEbqI5WWVlFNdkc+1N10FQN7oMahBIrEYVzPxOf2oNBsx+lQiwmJ67W+Y6sQnhBMXltlte/llC/l8YzklVgcv1w+nJkgcZtUUPF4JVXGgqqCqAqoviuH+DHIX5mKdF8sZMy5HsBh4NPclpMzXiHBP4eXJdyAIQUEu9LTOMIeVwVnpoWOK6iGaJTtOszloLOnEa20tzdTXl+Npc+FVXOzatZhdu7rwZwga4SYNLcLMyKRi8EB04U4o3AkP3x+azfoaK/E2VXczPDoQ3bCd+PSTQr9l0Y8UjPmYlTyYrZfs5KfDq/jLnvuZcc7Z2HdXsuRIHj8Z95IjpiCuKELpNxGq9hDT0Ii/SSbppjOJ+OPTx2iOJM6YSeJO3cNT/dTHKG2QZKomxWFh9JjriDqvO1vt6w8tB1lh73PdCbM2lxzhza0bcRiiaCw10OjJ4/mHen6mAO577g3QDChKAh5TI7lZU8hKO8jwms8wb5BxDM4gI2MXJSWdM+5mVYNgDIy/tZVNX36MZ/BeVOPb9J33An0SO1WDNVSuNIoosoby9/EYwlIoWX2EBu9BvJIPgy8Ra80U4qMcmOx6EG27OJIDUVE80LSZTbEzafJtR0Pg5Zkf4N1fyAP1T2A+LZ2ErEH6QVSN9wurWOZ3sIyhOExu0tNrOLsoj2/DxqHGW7BursIzJZmzcjfiSksg5t4FxOfkdArOdRGJ0x9iTY+r6SCvCxKuoWq6GGGwnqaqISE6Qvuq3drrtl+wTDf0u7ZH5/FC5Xq7dS+8iGAw/KYMj38VJ4yPE/jd4Nwz5zPB/TRhyhq+LHgOmEV7YzE7E/bis8QTFh/DOEnje8AU1ckYmD3wSfbkXoaiuI8bgNgVx1PyBDg06HKGzXX2aHgAOIz6wBfdA714ByyeZgB8tgmYDz+JcORxNM2E3z4GJeU0LBfdohOEd3FeZi74jtZFi7HkZGOfEgws7VLu3bgOKT4B48DuEfS9nU2fjOn8XL6NZp/E+gQLtOrbW9UcLj7/fL5Zs52k2CjmTx1J/uZcFm5YysC8RHx5hVRQyAhS+Z6XAPgxah3rt27g3huu6/WcARoCraiCm9c/ePOYMkETMGMIEdhXxXjwmVRKE91MH3AKD56jz7C/3nAWSe69DK2KIrKsCG99Lpb4kaCqvHfbtXhkA+To8RZ5chwTWnQa9tyWYUzscjxVUNlYvpED32zAarBiMVgoCDJYKZrCyIsvJLBoI8t2raFK0u8XOdGQM4u5YeEMvvuu455rB7z7tiAlRqPVhYFoxF/pJ+q87nUuTI3mx9LGY/adlJHNpIxsAP7yt4/wejrvps8fYFdhFfXtPgKyjKqq1DsDGASNlQNORtJO5uaSN3EUqNjLIgE4OmIuP9V9QU6+iFVRkM02wiJlzrn3FQJ+PwY0VEVh7hbdCBJ3P8inQ2/H5kjk/Z0v8aPcwDDVCJrK0cxwbqSaNK2OGDGOKFM2zR43DVnfYt59B+nND4LxHhxZaaTmx2HX1nBG3So+Co/g2zMXkhmRwsYjuh5TYW41VQcl/HYDYckORlhN4HdxqyOcusIDRFcWomgi2uBI7vrqXXzWaOI/r8GZEgaCwPtffcS9Dz6OZDR249X4tQyi/21oioK/uJjoK6/4v+7K/yhOGB8n8LuBxWyhX3Q/NH8gtG1GSyb3hoURV3Y5++PfokmwggRVVV+y1/ctcbEzqazUOREEwYgoGo+v9wEYjCLRcfbj1hEElcLSTXi2KZwy/rweyvVXnnocI6YmdRTJ5bsQ7/wetakZ5dAW1PKDmItexlSwGX/ejOBSQmcbpvR04m69pVs7sYGjmHFT8fHP7D1STbwKox7JRLL8MhW159fwzxNH8EHJYZ5aV820nCwm2JKpyN3IW2++jhGFtjx44uefCLdGAhA4LZKS9cVYZTMRqgNLwES1uYFpbaOJbA6jaE8N/UYeK0DZAc0sYsfKRTPPCS6T6+vk1jAbienJ+I0y47/9kuGO4ZyTeAFRlmjGDZ6O3dLpydCMEcQ0+oksKwLAVbicn/7+JjHhEh7ZwIA0GweKDlIbls4Xrz+M2yvz2t92YS928+PSQs48TTdONVQETSS3fRcBAsiCjIxMmBZGeksRrFrHuGGnMHLuA8iyjKIo+Fra+Pu7b6NGR/d0ej3CMjCeD6tX0n77nZy+6TBpxWGU3bGwK9cVstneq+5QB8q8Juq80Ty3YAsbCho42qLi1n75mu9PjKAvC1019BPMVpFFgdM41fsz3wybxdX930YoHctn4zWuOGDCl9IXv7OVTat+YvLMmUTFxWOx2TH+LBIQVVRB4JIDf+t2hDRjOIJkZJ+/hgJHFJdOXYfBHKmfi6qxdk020nAfjuIwqAKn1h9blA+a4J6mFuyH3ueJqlfZm7KGVJse9xRT48EX5iWhSiVhXwuyQ2S2YTfTF3zGazdfSTQgCSoLVzqpLK3B7t7JoMg6klNbQv1qKbmcyKzB//R9+b+ALz8fta0N+7hxv175N4wTxscJ/G5Q3FpMQXMBr818jZRzp3DxW2dTYarF7LwQgH2nTqbZ3c4HW68im0M0NPhpaNAzQByOHIYPew9fwUyQA8c7zHGh+hWq/roZ/+AIfrBdwFmfV0MPcYxSiCfkWBp3VdUQxe6GgJSQgpRwHr4FNYARWYhHSkrVdVB+pU9mTffoLCrbzGepfSnMiSR++Sb2nH6SHhsgCLT722hUXPT1tyEJEqIghj5tkolb+4/gJa0AURS56ewZfGQyULxjNV6MzD/3QlZs2IK3Xh/o4/qkMeQvY7v1IRVo9wSoeXQzhbvLiRoQjSQKGESh26cgCPjkADaLSPa0ngna3F6d1yTSGMk5k3ueHcqqTN9SN+3xiRgv/JbyTXvJz/8ZAIdJZtS517DujW9x+VQQBGxWI7fdMYY37lhP4cFGCBofBgxMMU3h02tePfYgjwSDMje9hPHeIoz2WADsVitoGnLAf8wuPlXF/IvlF/czZxDt2sarF6+EulbWDEplQc1hRJPuvq/1ROBT7YD/V2Xu1zfp6+yHtzeRZPQzJdXC7KF9yIx1YDIZMEgGHvt4MaLi45RZVq5cu4wf+qaR6SjkNulZVEHkKk3AqNpRZSOWySfjK9mPYgvjQGk5Bz74CFFVuO2OO0jwhRNviOH+2Xfi87WCGgBFpk/iKGJi9HTxTZ8NwxI9LGR4AHr4lGxGdQSQZ09D+1AgLL/7EubsMA2KT+VAwjoq3PsB2DPUza3nT0RVVR5/diuxpV6ejhyBMjqWGw4fYb1VIE2Jxac4KYwNAAk0+1ycT0uo3bCoqONev38HuLdvRzCbsQzr+fn/veCE8XECvxssPqzTd76w9lW+FhbjM1poNTiZdPgAowP38PX1bxFTsonh9+cCEFk/ELejFrsrAanWRF7RzSS31xPX7sP1RFCs65dpmmhEUkxueQqPvfhzl616HYdf427gmUG6V2H6vgiaP5msr/EG4xcETcUju8Ao8ezuD3n10A9IgsS1R05nTOsgPKKPddE7aZcWMwrwPTEbvyBiVKowSw14nTHUVE6BWx/mcJxES0Y6rz75GLKioqgqsqqi6kk3aILAIPE0DjIQAi5KgrEVdRGxPPT0c5iVDkPrZnK8+3nn8ks6g1E7Ti5oBz1XpjBgQQX7HnuSkUBKfDxWjxv7119wDqCNvJDW9Bxw6QNkTVUbNSWthMdY6TswljCrkRcta7GXuzj1+ZMB2MlQftBmIwka++REcpVkVM1BZvhWVq2+H1UV6Rb0C8GwXDPrm9cz9uNjeVR8moYEPJOiZ8a8lr+cqaffyerPv2RIpoU5z3wLgPGNr9AQ6Hv/IkRgoF/iNM0CRS5eu3klaCBpJgRfL475SX+EzX+nbeIfqaxzIWs+VFXTeWA0jZa6Rg5v3oPgrCU6fynl7+1l4ZAZzLhsDmZRDC2XTfFuQLXDueXL+K7PqZh8XnxjbCEStp+/bQFayLOacVtNLN5XFTLYDIJAjK8Mh0FBEASmhNWy3xnGI5eOJyzMrsdb+ryY1QASIpIgomLFLqicGRlFm5BK5fLBmEUf/VPLKJw+itdKH6WouppLPI20tuSCALffdjtH9u5h1+7dNDhdvPLq3/AmGWhXZNKSxuh91QQ9HVkQCMgBPZm6B8s44GpBNbkwaBFYIuOo879EdWIV5r6R1OaWMdA9HItkJqFmI8mNCuUJAgPLNbJXvEn96fP5+s49xAI7+iyl2NFOS9YIwnyncGZFJXFyNLsC7tCx7rn0z9wRk0OMv5Wry6u5Mza553v5bwT37j1Yhw5FNJt/vfJvGCeMjxP4XUBRVA7vKIcIcPnd5GkH0dBIbu/H+OrTMWom6kULbZkRZKIzfDrFo+CGduEoHUEENqsBySPj9e/C5gNbR4HWqcXg8xtorwuwz9R+TD9EDQo1M1t++hopbAExfdqhATq1H/SMmERV5WSziT12kcZgdssRUzFjGIRVNTO6JYc3ozSOqkaSvcUIiBjM+ku1+kAmsq8STdNo7acHBfplGYMoYTKbMEgGjEYjJqMRk9lEQaWCRZCZMTQRYedKDkQnE6b6OX9oZGh0+HFvAyVyImnn9EVDn3Grqqpn4GgaqqbS75mvqM3ojzLl5JDuVkCADn7VuBo/fdUEIsy68XHotT0MUPVZ/hpFIRKRTEs8Xml/6Ho5BC9pQydSuX8zQ8MLmTE0iubWNvrZtiAIYDFfElqiCuW9aB6ujvkel9SH8PBj2R/fLVxPlNlGvU+/Xrfmf8x12//OyKgY9hSnkHfxWUiShVjZhWA2Mc5QhoqIJBrwRCbQNyECQZBAEMjPzyM+4SeWLX881AMBLUQbK05OQJK+QC36kp83XdblQRARt2yCTz9GAyosMWyd8BiJwDMrWsg3dXowSixQ7IwmY+lmrnccxOpxsaAH75skDMVtn8Ktn+8JbZsi7udT09Oh358CO40DOO/TR47ZvxPRzCEB9xcAbzE/DeJNd3Cd+AAESURfPNydfO/9W64Kfe+IUjKFOSmIa2DCF72oBgdhWK1SsWIjh2ZdiyYqdHDDyVsFmpfkAlm81mBkVXU0GfTjXc0MtXuRlf1cu8xGnKsdR3+Flvs97NsyhuiB59KYN4ddqSsAUKQ8btkxkHxi0XWFHVii7uL9MDfCLgEG1DPaFMXp+f91j+b/JvxHi7CN6znt+/eEE8bHCfwu0FrrYcih2dx3y91kDI3tsc76R74hv9zGrJlFPZY3HzrIgs/O55WzOinPd569DnN49yyRNSedijelL1ufnttrf9oeuZSDqdeRdvljPZa7Gwt4+e9j2HnyHxgz5f7Q9tWffYfQpmDrF83FxRfie+cbxL27MJltoTpd81FGPPYYpc3N3Pbyy7325aknn8QbCLBmby3hVgvzzV5mnX4mCdGJaJrK/q1bMGkrsUYncvGFd/fazr5nviR2YB9GPnhrj+XN323AtYPQwGzpEs8yQJIoDCiMFIaxXG3jH8a7ufTSuQxIziHbEsbrNaswm01cd6q+RLb/wEHq6oqZNu3RY47j9dYgb/6WPqnTGTDgL8eUv1s4NGR4hLZFRjBnUDhX1Jtps04igBVZ9pM5cQJuUeJofhG5tUeYOmog40/vzDJ5/PHliEYfJtN0COraagSQ5RqgHknSSa9EUWPs7LMQBAFRAKm5iZgx0wgYTTQWbGJ5sUSanoTE9CQbr0zveKYEito+ZPPew4gVm7nykquxmIygaahKp7cMTUNY8CNxVQuZdNtfkTUNWVG5bPklAOSe9D7W8Gjat/2d8LajPHHhSFRNwyPLPFJUQ1rlUWICXvp4XZzUnsYwHMSeZQM5gKYECOwYiclZyKaxr+IQFayF3+EJiNhyssls3Y4pMhl14Omomh5sqqkqvo1LcdebGDP7DHTzWQumiYNz2w7c+1YhqTCOaMpPOYQneh4aGjsqthLVmIw/IwZj/yaWlC2iTOzHH1P1pa4fgKaW/hhLG4hOORMxrpJA+Pt47RcixYwkMg0c8+oZsD+GJK0GtXAQNQk7sHhjyRqUQd42jTKDSmMwzfak/SJ7phqwCp0ZVf+u0GQZX0kpkRcdy4vye8MJ4+MEfhdordcHm5iUY9MnOyBKIlovQZWqLJN/z90IXTLb4ps1yj58kKzb3upelxB9QK9QENGOsz6vaJ2smV0x69JzQ9/X/GPD8Q8CxB05woDde9h25AgYjISdfRaDrukulOYP6DM+nyjh8wVoLamh8LW3QVFA7CBAkvC73T0dohuEHmjlOyAHAoCJo59sQzHtJI1Ooy1Xk9nTcoQJgxIYHjWZLftWs/VAgJP7htHQsI36ehuxcfVdWjvOtVN05kxR7CENUQkw0uvFoWpgjWKj4OWLEffxSt4qVrCLgnAHt+Zkc/K400IeFYCElCRyvzxCWPQvybUEYmOnMWtmp1G2ZMkMLNay0O/W1njKyoZyx+0jeuzvt9YwvqqoIN7hZaDJwrXzcxg0IL5LjcFsqFCAzaROnITZau2xna1fbWKwfIjzxuiZOQFZgeWwI/Zsxs7Qn5stR75C8JZz2WB9eUHTNL4sPoI30sCUrZvxx6eQ5LchmjQsEzpTin1NB2DvN0w+5RIEo4nyn5bg8wU4j3cgAtD2wrxXIKwzULh5yz7MfhtnnXxxt362r9tBa1MJ7ft043PnKQVcfn1nQGq+8hwftXzCylOnEmdN4M5PH2Je0jjuPmUiCw5u4eFtdxDlC2MmU9hf3UqlC04ZBjnxJ9M3U2duXVOyguujqmgSEmlOnEb96iIC1nIOFZezPHIgNWonx8Rms0zS9moaxf2k0rOI478LAhUVEAhg7tv31yv/xnHC+DiB3wUObNCVQx1R+jrp5399juq8DZx225PkTB4OgGgQ0LoMnnnL7qbCvJDwRWaELWGEt7SRFmnnpU80EgfFIK0sR2Y9yvUuJEtndotP1vAFNJatKebw0TJWagIlbTK3z87ipmH6wKAhdKN61vx+NJ8HMUwf3LrrhfzXkRCQ8QMYjIQXFOD9+2sol1+OZDQi19eTN3UalmnjEE1mLrr7fs5Zcz45LYNotDQyvmoEmiRhkAOY6iuwW35ljVkDBIF9za18/chT9FMCRBgNQXZGAXtNMwMsYyEqGskn0EYTiuJA0wwYAgJhcj37Vi4ha8JZxNhS2LRrNZt2/4TNqMfHeNwOjh7dSUNDAeUVtUBCj90IBHQBQacr/9hCyciH1XW0TDqf9oFXsnHdzXg0P+9e8CH3fHwLK9jAXUfu5yWDwOzRp4V2q63WlWZt5l8O/BoNjWtZtHgpqqphMLRgsbaCNpNdu2LweIxomoQ1rfcMCqdBHwifv34sJw2I67GOv7VJ96uohGjUuz4bAZeXyyUrzZZOv5csKxgBQ59OPg4BtZuBLQgCC+eexL2ff4U/Xid5UyQhJAgfQkcQrKyAUd9P0zS4+EvY9hY0FIC1e/ZOqM4vUPWne1HbakO/Y36xn1HUlzLnfDeHFEcKmiaiaAqv7Cvjg/xqNIPCaP9MwE+K2ozNqy9vFh65k81HEnnedCcewYrEm7QRjSgLXB1hRGo+wDAljUQhwDO/6FM1IpHXXsa/O3xHiwEw9f3v0MX998YJ4+MEfhcoO9ipaBvw+anO070G37z7AqbAw6RFWImUjGjoL9nCg29TYV4IQNs8H5GbbFj++iCO7z4j4mAJilFFM2moUQYCrpZuxkfJ0D8B0PR1MWbgVNHJu+E+/vET3DSsD5qs4lRtjC79kMDjy1FiJmKsX4KktRCQslCjhyNE6gOS1IM67r8CURDAYGD8oh85unIl3HY7+UOHsW3MQGpSBuK96ELCDu8EIC2zL7dmXcuLxW9ya8IVuDcXo8r6DN5ktWH8VTVQnZa6ubiUS1f8SHl8IoLVihAkT/IpKlvttQy59xmGDBwY2qtoVwHx9S5Omvwnvn/+LZp2f8YN/faxkXFsZDzugBfJ1YZbtvLxxx2kYTlANuf2wAqvaroisNHYSyqroK/8eP36oGUIekieuegVtn1yEi2GdgaEZ3Xbpa60OniGnYOp3+9HVSVczigSE0yIoogoxRIRMZlRI29l1iyJPXkl/PDFhwwbNKjXq+bx64amzdj7vQ6vbObUjHuoe3xnt+0dujSCIDIyfBIEJ/QL91Sye9n7PAYYuqQYo2ndDGy3z8dpKzZSlprNRTWV5ITbsQcMIP/S+ND7pikBBKwU1GWi+gt59cmvgGgQJiBcq5PyCYKEaDDjbS8hIUYn7RIEgabPFtP89TchwyPmpoc48tUzx3gAL8y+kAONBzjUeIhKZyUgsL+9nU9MTRDTF2Le5cI+fpZ/upR2wUCgPYnaPRcSliCzI2IwtZZEEr3NpMSloCGiopGbEsEo21wGlxYywWphvtqO4vZz0CXzD0xcdlIq6VlpvV7/fxf4i48i2u0Y4ns2Un9POGF8nMDvAqfdPIxnlhxhznd7CC/ZECKKOjB4EhvUdmhxkpls45JDR6jevIn6qm8gOHbZXrEQUFUq330PtxFsokD/2+9Dk/XUQWX9EpyqDLKsb2Nkt2ObVSN3ShsotZzLlhVFaJrGusAtnGn6mr5KM5ba7wANrzAMAgKmukWY63Ua6AX7vqSypSOoVf/omJXWlh8gCaha/C6ft9gZERmNXTIG6+iI3b8fQdM48urLaHIAb2wsloYGxu/Mo6qyjY0nTaPRGEWpNY0H31iIqiUxT32UolaNMocfjbigMo1Av5ajfP3YA0FeDZHmgEAecQSikhGBhlOuJsLoJXL3fpgzn50nzSZNiGOwW0+RPdJYTWTCz1j2PUtLkQOdBlv/Z2q3cvTT0QyKTqe8KonDzVUY/NXYIzXU2gIMLj1s1ZOeTZ+ELJo89bgVmaPvf4bfX4/Tthd5YC2CIKGqum5Kbe0inM48nE4vihwHggSIzALUAxvZfXgbRMFrB5dhPLKJOn8tLYZ2prWOpnlZGXU/6LE/RpMRX30bSPDjmhWIP23CFGSWVFUD+2smsd6ToodeEAzBWLMEAK8/QCCQzrjjOLC8QQVjq6l346NfwkmIdQFcg/1BBs3gwYJ0+ILfj1IZyayZYbA2l1tyi/g+5WsuqjSSM6Nz2UPQ1JDxoWkaVy1bS4kjlrfjzMx78AEA9j/3A0LjLzocZC9F0Q07g3kEimAjpo9DZ/4Mtoemoaoyit+Hzx2HTDJHcrobXuFnXkX01edjyc7kyNfPdDKGBpHsSOa9Oe9x4083srlqM6BS6lsF6BlmohbAatK9cHPmjSPNkMXqt4oZOiWN86Ij+aqiglsjM7luTEaozZ98rdwjtHK+TSTpss6ly1TgtyR0G6itxZic9P/tEf0t4IS2ywn8LqBpGkPW7acRlYHNAQbu+JZZF1zJhSMH4ZMVrl12iJg175JW1RFsqhE9sBXZK9FW2p1lNMrpYWJRVa/HOjzgEmqSJoZe8iNti0g3nYZGd9KuQnEb003HaloA1EgiX4SH80W4A4/YcxzFiCKVB74+Pq/D8dBwvkppeCQPNf4VAIvqC5oZOgRNg6AYnUeyMtCZz+zG9Z1zf02jXbKzIPVcQKBueiZGSSXM7yUgirTb9Bn3n75rQjEIREQdpt/UF1ECEvpsHRA0BEFDECH66DxiCs6h3lvOupqvSLC0Myaxlq85HXtJUHI9YzQmezigEI3ERHMaotsCaBTPuD8oK6+haQq6YaP33+0ORxSsIGiMKKzA1CKSZzDyVLwDl9QZx2GTTdxTdSWJcjyyHBxoDQaqaWaLlIcmGxE1IwaTnuIr+1RKAn04bDd2XrcOjTDApXpwxX+DKHmxmCQ0VNBUNDr/KZofNRCBv/QPWMQuWTsAms7Tcl8gDNUFapcxRwjpCekZNjVmkdI4Az9McJDeUkBTiQ21oZV4TQvd14AGYy35/HjSORg8bjwWG6eu+Y6s2lKQJKbZZhBljsWh2KhztKAJGpoA5eLPHPA5SDa0YJKgxewjJr6EhDA7nWcrhr4LgoCzOYBUOZ6sL76AgB5NW5cRiSu804OWua+ehUMy+WFSd6I9KSARX5NAmqEKg7EVecAPpCZqiJKNBKERc4sZ2jyUrUjEnmnjO//VBASQrBL50br4YozJGOpaoud2/vqliRbBhnWuG1tfA35LCwmWU7BF9gsJuCF2iMZ1FYcTQ2JvgiAGM53EUMaTIErBevpvUZSCwnBSMB1aCtVFMOjeyNC24D6S/l0QdQNZ/y2G6nUco+aRx1BqGsj49NNe/qr/vXFC2+UE/uOwvKGVRlSeHZDKlSmx7B2bhcurDy5mg4QLjaaMgaRVFXH6BVdgMBrpeLMLU/QXkRLwk7vyDdxGsF6koEpGfDF9Ce83g9jUCYhGCz4kml87RJxRIWF6JtaBYbTYh2E0WxGVTqd96Ru55MYPZ3owhnLXoOsYPuX20AAWVXaAG1ZcwvkxV2M8SZ+5dnX5a8DBqFsoHVXCuGGfsKKxgccqw8mU6vhg9NQQPfTjqzeyVTKzYeZ4RJMR0WhCMhoRjEZyRJGpwEP367P0I8/1rmw78f4vcVljuO7drwh36Jk1D197HarZzr7nLgAgaeVuZlkcfDhHZ168cEEu66PgjlenI0oih3a7qG6B0SNWEJPQGZvQVpHHjvzTUNOaqT5cggEDlpgwJjj+SISUy1hhIyn9solW5wMQf8doTOGd2T2l336Ntt/OjOmHjun3kSNLqKy6jSGDXyIzc0Zo+wcffEBZWRlLr3u413PuUEJ+5JFHGAycDLx2xxIiEk1cfv9sAF65cTVjRsfw7h9G9NjGC2t/4qOyQuzySGIsUYiCgIhOziYKEpIgUdD2M7KtjCkpMuHmsOCt07NiKotbMDojKJYV4jWJ4YOC7jhNC310PBWekjrS6zQSdtZR29hxfSLQDG40QWBslItFdbGsFUYy2GFFc7eStPFHUpKSGCWMYYg/2LYKLrWdDQfeBSA2bRDGAfVQ6aBKjmSIw0u1x0BdXSaJ4a2hpR/9nwqoqJqMIzEfo1El/Py/49u3nIambbjsTlDUEDPrrn4iOzPCUbtYVULAwPSKJBIUgUZbFPHtGQjePMJN+4A2BEwomkTlCj241VXspiBTpZ8k4TAZ6Nuu0mIRMIhqkD5HYULbfK6ZOQJZgDen3UOrx4BkC1DOjx326W8Dp0F0Qf+g1vLvGyeMjxP4XcAq6TObZ4urGR9pZ05hCWgaqUdKMSFQbNMYYNVn6skz5vSQ1aDjh/UvEe82k0EtrZpIRF0F1G3Ap0ns0fozTsxjj/978ANLSkndbuX0h8YimqRurtISAQy2aFx/Kqfgg/MYfehd9jUcIOeGpRglCaW1GpumIUTGY+3TGR+hqioHV6ygas8eilr6QmYyp5w5mov7mnmrfRm7hQHEJkQhSbqXRYqMoFWwYUvoOTgTYJK9lYpfSWSpJgwMYcx/YgFrnr5UPxejGYO7JVRHE8EUZF71eWQOigqDymTE4LX3+HSRNEVt7da2PSEd8sFEMm6vm2VxdcBADB4re13judkyhKWE8Z3mJV5t5JSlcYRNTcGUEvRICYLOs9IDWlryAIiJGXL8E+wBJpMJo7Fzlt7S0A5eM2FxnVk0ImAw9J7hkxlvhzJ4ZOodzB0wiiM1beTVtDMwMYwB8WGIosBba99i0fb3meTejq+hEcWnLxtpQKrTh2jogzl8GBrpFNTkYTSrnH3HXOzh3dk4G19Yhi+vhdbG7lk+NbJuiCyq04NlAx6J5WMGAgPhND2jZd/LO6DWy6FUC1aliujqznOKTo5mVdxQ9oXbmJx3EC1lNMnufTQ3i8w+843O63NoPTX7v6DNd4j2VD3A2+M7SPOwXbQLw3DG53DaDd1TRAe/PQPZGcNlNpGAasHhScVQ7kVUYeRV2Uwclcg/blvPyLS5TJzZPavsxW9PB8CcpD/rT1+VxLis4aHy5oYWdn51OWLOIXxeKyOFBVS5dYNFTPuAyalpyO7WTgG4oJhbSFROVVFDZYouCKcquudK0z9VVelSroKqoHV817TO76oa9Hrpv7XQ8VTUYFsEOXM0VdG/q/o2gjw/mqpSaVqEacyx3DW/R5wwPk7gd4Hp0eFsm5DDrcvWsOSaP3NvrzU1/D4Pev7gsRAShlLqKcN/1yHs9niKKjbTWLicwrVHMAsBDBHJmOtq8WvRaJqRinoP79y+AYOge3QRYdT8TCK9Kv3tFuy2cAZc/TVHX5/GsLqtND6TiXDLTuwuF+UkoRw5ylMb3ic2zMQDfziZ1159Fa/ZjCQrKLYUqIXPn/2E9ppEjs5LASO8vaeOm8bowXMGQUAVex6YOyCJAuo/ubraKugDmP/l0TyaWMiTjWcBOokbooAleCyz1UD/gMDuJBOVTW5Som2IQiQAotg9a0YyWjB7+qAZAjji40GrA+Att4tI2YRmBasG6R4Dy4VoRuXWIdd7SPhjZ2xNT2fY3l5Lc8sCTCYoLdvE0CFnh8o6aMhdW7fRunAhSU8+gSB1j7mQJAmpy7a9W/MREBkzQzcGFVlFQqDdL/d6vWSle8r03Fc2hsr+cflo5gxOxNDuYebueNrMR7FGx2GK0D0kgiDQUlyEGijA01hA1MCh2MKyaSjqQ31VyTHGh6aqHDB3vxLTI53cOn8C7qYGalrcLF+zAaPsAs7sVq+mbximRi+n3DqWVR99g9xo5aoX38TrbCd5YA43v7IGqdZLMaPZn1vJ/Kg6FNXIno9PB1VDxU9L8lGIAbENPDJ4EcjzefG2vE0qD3XQu3SHoKFpAuvLZc5ujAN8gEBGRgPW3WvYtVMAkjFwLBX93V/pwcefr1vDZS8vZOvdHhqiLEhKACkQIPxQLjGDnTTngMEYwB2IwGYSqBeu45Jhwaiv6JRe792/I6o3r8YS2ef/uhv/KzhhfJzA7wbpVjMfnjKVD796HYDUmDiiR8/TBy5BoKr4R+rzG2mo3kJlSS0tzVuJCB+FxaFzLvQbcjaiIBIQRUzh+kurX/pJ9Es/iS+c3/P9FhNnZ8pMWXeAmqROT4MCDB0Zi6fFz4s1DTy2Wl8e+GOdibmAzRaJ48qF8MZIYgKtbN/0NmmmbN7jInBCpVGl3dfKM6+9hcFsZpzNxty77mLFjyvZtm873tZwMka28Hyzwh3x6RxpcoWObRAF1ONwb4BufCi/YnyEiQHaFQNPnZaJIAiYWgsBuCVsOY/e8yDn3XoLCAK+Lvs8PbU/c/YX8cjGIt6ZPxSjqC+1GIydmUEV3y4lP+JuNKsfzT8cgygxwBXDYXMTX9pVwMsV3jV8V52HwXYyA2xDsQFto0BsqcXf5iGvrpEUpXsKbCAQYN36udhsbXi9drIHntp5P1SV9QYHtrAonl2xErNooP+LH3Hhn7rzn/wSPo8+AMbE64O+O7hsV9zcu9tIDfK1GIJG2TWTM3n/5+JgP4KMqEV6Gu8Vz79MfELnwHLNe+eSKBmJOaJfVVufn5gw7TIWv1yLqhw7GKuqSoFZN5buGWHi1otmdynVCbTyDm8h0IPyrSgKCBpsXnOUAYcTaDU4iUnt7ItU6w1936ukML9yPcRH0247GoyrEIiqHYCjNB7l0+3kX5zIoxkNzBUVxo95jJIKGTQVf0sZhrBEREn3zvQxNHJqehW33/0ar9+4Rj9PqZXaciO1GFER2GRt4+j+XWwVlGBIhorOyKMiCBq1BdVktZST7GpEbrbjkwzIogFfTDyZuS6kWiBBRnL15cqzvuz1Xv0W4Pc3YTT984KEv2WcMD5O4HeFGIeDnKgmalwWLoxfANd+ECpbt2Aj9fmNHK24H5NDBgs0+DdCMEv36JLH8OcNxK5E8/RfP8UYrzJ8TD9mT5jMwaoWIJ7vtxrY2ieVJmsbdzaDEuRwyN1dQCBco8RgJUwSaVdUNjq8XORuxYBI1bc3Egfsm/4sw0acSUvxgVC/xhp1lkxFE0hSFaZefQnulloCHn1gO+emyVhtJiZt0dNi2yWZiuY6fQXe18g4+Sht+VJIh0Yj6PJF/zC5q2khncLD+1BUVadN13S3r/5dw6Z6SRZ9iGIKqzbtIUPMob96mI/k8/HUVvCPJ59AmH81O9z1bNjuJPLotww78jrfO3J4y3geRY8uo9FhoVk5hVLzIZqiahEFgXr5MF5XFHZvFo6Y0/nQsoJlyeuIb7Mz0+PhobbT+FbRB9+4QD5TTFkImPhq62d8VajTZ2MDMUsg+vMHUTQNv6qRGtaXM8UwbLQRF3u9HgQI/PTxXt5wudmSPRDSdA/Gn/e/RkFtOM/d8wHT5o7BYNDrCm4bqq2FAwe+QdNUGir9QApLN+1EtKegBlRqIiXaksw8v7tUpzlBQwh67RHgQJ0H2ZiGALS2NvOnuQOZNiAWDZjaX2fa1QJ60IHZ1hnHApC1xoNJ1s+9zRbAkuhCDHJgKMqxVOCaqnGhS+WiF04h1tEzJ4seDNuDoSkK2BWwr9RTW3c7iuiqirPytizm/i0PFZHllw5m33dZOJs9TDuve5zN4StORrFrnHLzh8StvxmDIRLtUytpmLF7fsL0yg34ARMgIzAzOgq7TTfibnnrWIKv8to6nnh5BzRPQ1ivhlLhuyMWJg5l0ewwhs7qZJ/94YfFCPfdS8QCA003yWjqr6WK/3tDUTyoqgej8d9f/O6/AyeyXU7gd4Xdy35k7YdvMyOhiFF/WQhxnfEUh7Z9xbKXPkGQ9IHZZNc4+4E/0dZcRlWLToO++93RmExj8fVNxV6VgDOskdufmMeRmjKW5h1mZ1kLuwt1T4lmhkkeA5pPxhGoY11YHLIgcN/oZJ7bdxBj+B7M8Su79U/SNCQNRAQE1cpJ1Sdhl+0cD7E1UxAQ+Xqyg7zU7uv9W7deRIav+rj7vxA4n9eUs49b55+Ff2Q0aryVXTvO5sgYEaUsguL1OUzYsY/i5FFU9r3yV9uosR9iV8anmCUHt9VeTZYvjYqdL+CoLEBCwHHay6zNOET88Awkq5FYRxR76pdS7M9HEgwENJEfK/fSGns7Y6xussjD5vExNusB+LmRHYdcfDFdYvzRQ2zLHMQfj7wLhT33S4gqZODsZ0O/A84o3PUDacw7FX9bMk+cH4X2K8taAPPXv4EY42WKYRwJ4YnBuEwNoamRA1t+ItaWQrQ5kYbIWvRsHagvPRra/6c5LVyfUs/E7JUseLoIc1gL0X0COgGtqHOAVR2RkX0m+ieWhbwRQpfUGwGBfXtXoSGgTJ+rZ1BIEqIkIbSamFWXhIjAN6YNNCtHyRk7Qd8vqCZcvKsYaxcPk6io3BCejqoYES2RiFYDTau/xWM8TPilc6hWviHycYHIPkkIo4fjlfYSqRagikZiPXWhdlYbknEPfwpRDPLSqAJpPiP9IiCAwuWrvSRHuZk8rD+qqrFr6Y8kWNuJtbhRkDgkm9mYVszZ5UYy+o+koV5iVGQilZXVRG3fRsuVMqBhMUwgyjQKu7VL1lk3srZgEnvnf90yikL1u5G0ddZF7CRn65YJK3Rs69p+sHWx5+MIwfuHoL8LEECW2ymteIbxJz1KbOxJ/BZxItvlBP5jUVtUAMCewHxca0oZNScRe2QEXpebptJgnIcmYXJI+NpkIqIHEhM/iqptj+FvSiBr9OVU5kucfHl/1j1bgaM9hrf/uJjdHGFbRA4eKR6LIODVNAQfbBFlsALWeMI0D/3NPs6YMp7n9u3HZozkghGPoCo+YpsOEWcUUDSVgKZS3VLOR217mZjRwsjUEUHxNoLBaqBq0LRjLdWN6YyYXo1gj2YyXsqNRhx2LZT8aCsK6GQGQO20VztfaqERSeCGLU8y3b0XYd7LCKKIKAp6VoYoIogiTUve5vnWQbRJcTxz/hgu+lJfcrl4eAzzsqPQEPB5/Fz3Yyl3lReSnGygfqmZpI/hgsdfoOGKaLgCnn5R55HwG2UwGXS2ThEEi4g9wkZUlJnGXYfpXxvOJUtaqYl30z7wU/aIInHNxUhBz03FXA/nTb4Om62TPGtkzqTQ94MtlfxYOZfrtDdoYyq5jOKIdTBvVrYRlqzSTzFz0Q7dazKwyovWfDk+oxuLbAKt+ysvNm0nQwYvorJhB+d/EsUG8x2kCIv5aZKZrEl/4/GDhZwU4eCRjMTQIBPSORbg8x9W8V5aOlHWYdxaqQdDthjaUQUNVVBR5WimRs0hPkoPIjzcspWD7T/zyyiWS2PPwC69R3RCAtF91+BpMdPe6EdTRTRVQFNFRJNKWPx+yvKC1O5BHhD9o3MOKaDh3b0VQVURNBVBVRFVlaXB3+FyAKvBwkrNQIUSwcmmApoiY4gPRKDhCw2Ykhyg6b0XsIz5A8ZUfUnN3vdqhMBmii1vgwpim4m2Q+XkDN3e699kXtt8nvu502h+CitDMdIAqKiMNO9Gc2sUbNWXqyJjbfiwURms3xxZhGyr5JuBkNNsZZBnEOs81Xo08ITxkNd5LJO3koiW3tlm/2eg/eLzvwoT8FdGjk6EnuWpflc4YXycwO8Kc2+5i8bKSmqPHmD7ggNsXxAsEMyg6S5uTTPha9O/b946DcmovzRKN1rwtRVjMA/BbrHRHl+DJAm4a+NYF65TWGdRTYUxEfzHzobbBSuRGWmkJsViFCX6RWTwwPBzj6kHcOjAIhZsOUpCrEzm9Et7PhlDBax/Fk7aCEnDABjxiyqujH4gN+C0zyNh5lU9t5P/PmP8e2H8lGOKWuvdDPJ+xfZiXcV0wohL2ZyRxrbiRuYNTcYUzPTwe33wYykJEeGMSU1FqdHPf/amV/ji9MfoV7qfYeWN5NmPUBSTCZoRVQCDArZmFX+jk1qciCY7BnM1lZdMxPDzXsKLa9A0iHB1vrjrvnyDqthw+o+ccUx/AYyqEwC7qDBE2Mqp2mJkDORrA9kknY4xbAgxtRPw2Kox+2IRELEEbCwZbeOKvq9ib3CiKWCLP4JkMJOQ8DbFbSbeMV5LiqDHS0SJCaTF6R6paLOBnOjumkFen5vDB1YyOLKZca2tzPIPxZjiIPrigaTGdl9eWXPdn4lHNz6Mg5s4fcbFZOaczZsfL8G3/D2aDREYm2tJtKuYLRYu/tPV3fbfvW4lNcUNJMYfxCmsZ9oDW3q+z8Cyvz5HVXked7/zXrftmqZRvXUza956nTLJghbwkyvrcU3jTz2fmzy6Xk7OjjyW334WCx7/iAZjGwMPHaT6iW0IokDiPSOpeOAHLIYUpo3fxeVvzyTthmgunfNnXnniAxSlBYtjLhHWSC58Vk+bfvOejSgDozlwTTYtbT4OvJfPEA+Uj4tg7MQEZE8A7eO1TM2exJBTJiCJApIoIooi7qpm/E1u9tTuIrcll1fGvoLX42XHoh3Yptn4puxrHhj3Z05LnwMGgZeeeZOIaAfXPjwulLbejayNzk894UUj9OMX5Wo3YjS1M+U5+CWUFq/pCtCdZR3Lnp3XXetCFte5LNqlLLhPfamXjZ83YLOeCDg9gRP4zUEQBObdfg/v3349AKIUDfhJzp7E2DNOITU7Hclo5KtPvsJbeIRGR1+EuibcxV4YkYO4fSBosODJvZi1SERNpCkYxp9IOz89cx1bjzby/Z5KVFVD1TQUVUMFluyrprjBFeyHFgo4/CX2HdrHgm93cQqn0Fj/A0wvh6geXjim4IDnbT22LAh7Tjrs34bjns+Oc1F6D0h1RFsQBMi398cQTJlNjrRy9sjUbvXEIBGaqsKAzNHs++OtFG5ZjpxqIq7sct56Tsagwsi9f2f8FwvoN1IfbCur2xGNIoqiUl7ajtvZKdWuTAFJVjH5Nbin090/4Ocy8mLf7dX4MAt6DMGgzBuYm30TpS357K9eS2T9Eq7mRZqGPEpY+iS8/mwEScCrqbxW0UBFjIHHhWt4PP5BUuyJuN1mDAbdwMhJCPBx3xSGVh3liX438MzJfyQQHJzagxo9TRX7qKsrpGX3l0yoWMFIdK7bS4Dy05eRMGZkD70F2wUVFHsewm+vBlGhtO5rjlY8zNCEUdTMm0H7xnwchdtZEW7g3W9mclLqUCqVBHYfOIl5BfUIrnAgEVvW90T2aev1Xq59/ksC1S5kNcDBDbtY8eYLiAaJ2AGjGP3ZOwA0DI/GTBS1lji+u3oo536wnzsXFobo8YxmD2azGVOCHaHFpd93DQRJQLSYEVQNQTBgtEfiEyQEyUZ1YRmKoj+jfu9hjMnTMdr1NOkAZqwmE0d3VGDbUMBABConxDB0UjhePCgmPbalsrmSmVFhoSWS1qI6lPeLkIBIiwyZYCtUkL0+YtUwduzfyffVL8MRcA0vJPriEQhISAYDZmvv4pL/zvC2NgANGC3/f5ILvxWcMD5O4HeHqMRk4rKGU1+wF2dafwSzmQLFTf7ChXqF4ExDJII/5NxGwuROHYX8k0pZ+9NujFYVQQRZ8XNkRzuQwil97SxYvZPMxCiePXfYMcf9U64TGmHvnzfwhdYHinzseehHvTC05CsgqAIXKpNQBY0Kw3aw9pz2izn4EvW1936yhuCwEXCDqZfYEUHo5pbvCkkS0f7aTP1DfyczqveAvQ4uj47Z4rBbbsH9xRdcU2ni72v3c+C9oVCnGwWqqvDBuhUsXy4zraV7lkrGzD5YYsvp678KDY2+W18EoPZ0jYUVJ5FzdAeLx4mMKbNTcf9GfMKxWR9GzcB34ovU5dQgCAIZUQPJiBpIu/9KftxxPYm1D1IqjeCKqV9jECU0TeOvG9owI9OoxvGWeB/DBIU2dT+j1SKmAjt3ns6gdNiXbmI4a7HaHsIl60ZHkdtHTUM5ie9O7WDkp8SeQWXGyWSnnUzMsotIFI8NEO1An/jzOdJ0J+OHrMISlUjR3iWUHP0Sj20XsanbGD83Hk/LMFa0bQbqOZS/BkPdbVxX5CMk5gJMbVtFoLB7zM+hfXuoKS0jcZuZLDmFVfJ+nN4mlr+uk6spfqjd/1Oofv/2GApyBvONYwq3RR+7Jv/g/An6l15WEBSnE62hGYDyaA8mKokbHIMj9SL8rQI2g4glXcNVdhRBlLAJraBUUi88ijZVRFP0Z2zrfh+CAF6PDTiXo7WlvPH664zNLyBqxnSM1iQkVcabYMAwOB5qoc9mK2BlMHGcXD2MdnRvjftgGUphPHbVgCz3fh/+3eFz63032/4zhuX/jLM8gf84pE+ZRpmrnZTU/hgMJkKhYsF4iNr2CtqdjQhS97fsgL7pDLghPfTb6W7ju50fAvDxUZGPj9YCtex9IJ6I8O607B2ozXDgCrgID9OwmQ2omhYiHlLRyYyammsYVzmQ+AGXg6WXwCxzcLuv99kuQa0XZF/vxsevLEULoohosoGg8O5Dm1FjTOSMS2Dq5D7d6gAoWqc7OsZgRHXqSyBDNuxn16I12O69hed/+ISD7ulc4tQND8vYGOw2I4qm4fVlYZJrSZx2K/n7fgi1FR7bRsT0Em5p1F9J+30wtthPxbiuaa76iZhbNFLzouln7O6dCTNZuWTSxyzP/5T0ykfIrd3FmKRxvFNRj1vVuCcjmdKGrax3RVPj0mgRTqdCK+KGX14Po26M2oIGV4bVTP7SR0gEdp7xCTmDZpJhdZABBA7t0XvWRcH4lxAF/ZwEAQxGKwPHnMfAMefhdbdxcMcb1AnfEJG5ijfEu3kl703yLXBdUXdV0+nxLyOb4zB4YfOOtSBroGjYVrgZENBNoiZTG20kg1CEIzqNM+68haT+afztpmu4/w9NxBubeLZ5I4f9CaiCRGpcJDvvPwmrxcTynfncvbiUyHBH8Ep3Ydv1yCge8Fc5EQQxSJIF18f66Gfx0FJ6J/3nQd2+c7i45W2oAN7X970pHpan6PEied/+I9Rm3MDtTJ01DG+ghf2evcTV1zPhq68RNQ155Uo6mFXssx4joz6RUxMnU2mpJ84XSWWKi8yKyM6LI6fhe7eIsxnBgbDevYT/7vA6AxjNEobjCBD+nnDC+DiB3x3a2trYdeggcdmDueaGS3qsc98392E9aMUje47fmKpxat1KKrPGssI3CJdkI1Nq69HwKLAKBEwip9wwCtC9BHV1S1FVHzEx0zCZOqPINE2j4s8b+KhiPds/ePaYtgCQfViT4qkrasJXtTgoAEeXT5hcfYhngJKXskIkoEbB2C2eMVyWaTVFc+GypSEROU2g8zsCqW2NhBXk4gsbAA1e9uW1sfqNP6EJos4jIohcoInsrLXjWfUOJllhao3OX5E7TPcC2fz6zO1gUw7zlc4ZeuuOBrzBDsUOsiOm+Nm8dQwA32SMpbYom6zMw8TZSiBIGz7I6cYV4+Kks7uTZQE4i0toySvHYDr29SUIAgEpGhOgBrw8t3oDL4m6Efd6fg2QHjr/gKjha4vBF3AyfuImvt77Ip+6h/OXjBGUtbThyf8ZUYvnsm0PMq1qGW7JRnrSMNzNDbibdN58sbGMGECrK0E+mq+zVqpB9kpZAVWj7XA59bXzyVP3Y4mo6MKXrpFomkRUTF/KShdStDWbv0anc1lWKU3mOqJ98aHzqrQewlPnIaLCRnJlYcfZArAr9meiJ2ZR2lyB0ZyPwT2AjcYIpO8+YeqMqQy94xkC+8sYdPQv3Bd5G8ssQ5HK3BypyNeDjt0CdW1NWFVoqm6hymDG4w2gqRqu+opQH+r+tgcxKg0xwoC/vJxMt4jPG0fMiFtwlvyVeNcGGsVJxKibqRv8GFpEMrEbryf7hxYq+3akBusnX583jsaJIn2yBjL/h+76R4bZQ5F/2q9fovJN2Aedx1lNM6l2NJDijcOQakAZHIkWUEF2oxls+Le2YXfDpIt/m1kiAB5nAIvjt50u/K/ghPFxAr87vPTSSwBcccUVHK09SnJ0MhZjd9G3tPA06qnHIBz/T0ANyDQZo1ggjwEJJjnaefjSaT3W1QS6sTwePHgHtXU6S2NS4rkMGvRcqEwQBAKCQqMgMdSa2Lm9i9VQq/hYJ9fjV/NJJ4wxBtMxEl9NkQLvOMMxdllW0QRItiUQY9UVazd4VNZFzmGONdBpbmh0MT00ioUmJKOEpnoRRAuqXEP8yEkoioyqKGiKinJgA1GBFtKHZHPEVIevsgExOga1vz5Lr6+uZrfPwmRTC7kOC1O8Ept94RgljTMCZkQgrPh0GLJIvybhr7GxZBtI0Fo4hjMapvB4yXDejfsr7TY/kqn7EkPo/IIS9Zh6ToFtaj2ADWgvvJrRAmR7n0MxZjFJNCEGNVVEARZWnEcdMOZzfb/JUQkcCruMiwsVBK2Q6g0XkTn2E9Jb9Qwqm+LG9vbwHo9p3nEn7OixiCrvVTS2zGfLYQDdQLOJMDvciAaYSKI/N5EZpnGyfBMW7c9YxR1UxsTjEmBnn2W0WWy8+7UJ2QMyL3VrfwCwyjmLxrhYpk7bCmzl5g0N4AWWPc9Tg59kRewUiH0mtI+SYGPuawWh3zGKwK3tVg59Vsch6oB0nPZoiv9WTGSXYwmiCX9JMUWzn0J8Q8ZMLeMyL2Hj+ocxxhs4Vyzlp3KIO/BXnFVmvnCfRmH//qAJCPGbEVUjaCKCJpG7+xC11WtJpst9FrWQ4QGg5q9EyzmXJH8sT0e8x5imh+iz1QG0dOlVG0ag1eIjNaVnb+RvAV5XAIv9hPFxAifwm8XUqVPZuHEjr732WmjbqZecyvgB40O/YywxuvEhHv9PwGAxY1XchMnthIkynz90Wa91NUHQlWKD6DA8AGSle9yGpmnIgsKImOFceNHrPbb35v5PWbf7WUyu1VS7VuMf/ABPjjgfs6Gzzwt27+MVXxlOVWT9BWvZVraIO7e8BPi5JftG1pRsZ3eYiDt8PFXTJ/fa9z+v3gWpqdz8yBxkRcZgMCBKEh6/nx1HS2h2tlN4YANZo0fxQPzXALS8ciZPTnky1MbRH39gx2fvcOd5Y0iapGfWPHf/Es43NxEflY2/zUdJi0btwnf48990wqnzpSw2LllLmtuK2NyHSqdC6RCBic5MBl53So99VYPGh9CD8SHLbjJ8q7tpid3lep/Zpy/AaulOzLXsQys+wcNlGdP4tGQDmVpfnrQWoRmzQJBolSJYmHsbhdZUjpjS8U94UD9vT4D3fy4BBJJo5GnTexQmXEba0Lk6IYco6umqooQgiWQcKuPQRjjlEgPhmakIAqiqhvyGrpzcQcolCQKBMbGI5RP4aEQnP8z7k16EsCjKDz1P+A/7sX3/UWdmRfBz8uW38ONZ8/mu2chGp5H9Xc5zokHmvIREVrW3MywpgjeO5tNqg9cvCtNp9zWNhsKjtK3JYOAsE47ICH5eWovbGM6dUxp4L9yOSTSCV6PtoddQWsqIvuZqqvgHlvYYfD4fgXSNADWctvN02tVFbNmbTV1UPAOO5tMS18pm2yyyjK1oBpmMxGxKao7Q7knjqYoX+XnMTQRkA4bB80CS8BxoIUAmluEZNBc40RxejC4rN3qncHDQXobImZiDk4ZAuwvnD9+jKX76L3i71+f7twCvM4D1hOfjBE7gt4tZs2YRFhbGW9+uYY04lHClHemFt9hl/yiU5ub1e7D4ZP7xxK2dhEGhtDc6VUVVlZaYNiIyn6WRDMa//4NOlER3LwWAkJmDaJ/Me99vhYoDnHZ4DprsAc1ABSr7pNsQJQmpQ27bqZBv8/Dlnkc5Z+h9mAzdvTMDI5L1dgUjmhZgxcGnGBAWy/UDO2m1beGjeTDpS7LHrCLMEsvJA65mbtFCltcd5fXDf0GQIwnEXooqHp/ITFBkNJMJ0SBhCjKAtno8vHTv7YTXV4Xq1Vs7Z5ZWQ/dgUqEjKLVLmqJBVVjbKvHsX0chShIvPLsVKvU4jh3r36KpZQXp/RTaj5zG1Zn3ES5FES9HoXkVGp/6PJip0523RAmYgBgEzdvt+GXlH1FY+Aya5ic6ehrDh73H2nVZVNnyGffVGE4W5/Py5U+E6md6sykw70f0ZQAbSEqYwhUTuqRGjyoj4/4lxLa38s1ZDrIn6EtADe0+1m1cRazDRHqGBoXv0T5wOqYpZ3TrjybLKO52LF4LbPQRHR1JTJ++ofLiyQLeXbUIooApGGwomXZhig6m0mrwxqinGJulG2EtCX2Qxf2k5+iqwt7Dh2n6/HO8Bw8y9Kef6Lf3ENfkbQCHviS0N2IyfZ253Lj3YXbXruLRSz8mzBHFtpLP2GnIYs6I00N9OawKrFmjMHR8KglpGaw57CVQ6yFgdLHe9y45UiS2PcNodZcRGXDR8MGHHDmqZ9AcWLeEvqcaEQ0BtqcM4U8FH7JjpN5H2WBg1vKfUXKcvDzwXqYYj6LUHURC4sO6wUSYmojqrz8P6p9fRDTYaXrlcwyNIgn3XUQi0L4hl9al7UwddCrhs8fQvqmS2sV5OMZGUv76C1i8TaR++jnmXsQifyvwOgM4onpmrv094oTxcQK/S4wbN45PV++FVmiTwgiINpRAhzKJgEGU8Jt90FUwNchgqLNG6qaFhkbqUSsliWacUVbsvxhwu6I4KhPZbKdZkWgYMgavr50pO1aTljQEo9GCpsgoioKq6v8qXXn4fApP7tvAW4cW8PzUx3CYotlZsYy+0UPQDLrxoWkBNCTMlnTOTp/Q7ZiiICIJYDJ0GhczUs5lcck3jIycyKeX30/y+n2/er1ERQE0XvvsU+oL8lBVFXN5EeFuJ5b5FzNz3DgWP3gnUmIq+8/bT7O3mShLdxrojjTJrsbH6VI9Cy2JlB4sInPYAOyOfBLGLGLF9++C+RAYJUwJLTQ2x+I1uvDiAhFEqRFRCnThYOhQCdUQBR8WaR1iu04mpaoBdu2+mLa2PaHjljRsoWDNKGJEaFMTSQ/Es8r4A/d/eRLO2jBmjUrC0RSFkiLzcfXHALR6jg1WjJT8jEqJInNCp3aMPaiv0uD0s+RAK49aoLHV1X1HTaP+uXnE+7diCPQFXsTVphDTpUrmGX3hDN0Y2fbZGvbuaia65S0yw2L48qw1ofTm0D0ySwhWjUBbM4JgpPjsc0JleXOn4PtjKt/V7wLd9mB468+h8lE1G5m04WeO2voAM4iiu/5LiPOiwxLXNBxGkb/wMKjQqkLrsK387Z77SMhr5ezEaMjVq8qeKL4LXMpOw3AqktOYHv4+Jxc+RZs/mwWDbBS7B7E7XBd626fGk53ZSkNePv3bZIojskACjzkGa/AZdtfogc7ewyW4dhWh+pqBBKrydvDU4ZcQW9JxmG2k5cYxWPUR8+rbRI8YyG8dXleA2NTfZprwfwUnjI8T+N3iqRvPJfqWmxg1/wLOvLDnpY1fg6qqvHzxmZzV/2yuvOi+49YdteYHNBp4IjuDawtUWh36y/RQ4DATL7icmWPPprm6mdIDBWxb8CmgMSpqNGfPvJWHfn6Ia9Y+1KW1RaFvt435K38YfH6PxxQEfSBU1E7l1Zs/jwFu5JpJVkRRZIQikSv1no0BEFWaD4An7wBan36IRgNK/0GcfNFlDO/XF03TWCx0+np+aXgEOwN0Gcj0HwAkZOqEVo4+e3FYDyD4hqLJ/YmPPQtX00cMtKqMbZoGYe1oPh8TLX2JuePqYw4B0Fz0JZGf/IU6313kF39Ba/FD3crL1TgEYyya6sFHFPPHPopjewMr9j+HcOgTmmwZFB4cxrS0Uxmz7xRiLmhne+V2zhhyxjHHEgWO4WuxmgxcOyWT0kYX5oAZKiA8uARUuqeM6m/fIl48TF9pq35ZgotALiGR3mBMk/m7/AhoEONK4r6vbkIQBERRQhRFRFFiVMIqeD5A7U49WDcm24D5iG6guGYr+GzVVCaYSan1wUn3gSKDJqPKAfaodq6L0HggmInaLMR0O74aVOft0L3RVEAQiMt+n/oj19BmHE94YBuxtmj84yZw6mnDeOmS6xENSWiaG/d2GxUn6UbDEUc/MmJf5pLDdVwdiOWHNJkjBj/IGilT4IG5D/DUFfNIjtAIyj5S3+cC0jquRXgbgbZwGj4qJ2Bp5+i0+yATHqywMvfoeQCYNCPTA4Opm/MIKbNG93pdf0s4EXB6AifwO0F7Yz1hiouhA9J/vXIv6Jh9lu7aCRcdv26VoB/H3aoAAhnl+szT0aCw97WP2K9+DprOWyFKdiTLBJweP9a8bTwePYvlntX4NR/TrROokKtZ5ixmWNN4UrdaWLY/KEQnEBQ40z8Vt0R09d3sLF7OfoOJhkYbFxib+X/svXV8HWX+9v+emePn5Jy4a5NK2jR1pa5QaNHFYXGWZRddFllY3BZncXcoDlXq7i6Rxht3OS4z8/tj0qShadl9nu8+3x9sLl4lJzP33HPPfSZzf+Yj19XQkcwH7wf4yPohFf3TIMnOGSsOAiryceyOx/QojmVXrF/weyJi4rsKMv5RWoOntJY6g4XwifOQ3CE2fb+s65oFFVKKRfq73Pibm9CZZ7Djs0IOflcJCNicVmZZ9bz80n4EAaIS3LhiIznvrC+7+ti1ZAVqfBnvXb0egNq/fYslydVjbtd9+Da1ew/jDszEr8QSq3+aorxnsIXpCH6RjTHcT/KkOiyRLoZUhlCDfoobz6QmLI5Fe49S3FFEtus8jPaRWHUKzqAfa50eRLh43MVcfJIvV+rF+AB44KzBADjbmuFFkATNwKj/8UfG63saugUeLUH52ALfG1pbuq/3oLuos9S18//HBAMjZGYAyd4LUBCpnPcD0i2aN2/atEIkUUfjZxdC/U8ENi3HIO8HQD5vOaNyJzBCVsh8cjotEVEIoRBM/7HrnMd07KTOCiJXSEZUFXITp/LykfEMCWqGlIhC4BhLqFyDLGshudK0S0EQGNDmZ2iHwCVHJdKVOJyLbmS20cyQN1/nBleImDCVpoYazAGJ8IwELvrzffDEy0i67vJSU3gtwQ6tQql0yp1d269wiAwLDKVUqmdoSPtbS1gw6KRz+muCqqr4+3I++tCHXz8qDx/gy0fuwxEXT1ruicyTRTvr8XuCCKLAwHHx6Awnr61XUBFaTi6rfgyCKqMKEo8VNBAu6UhpaMMTBhYniLKKJTydIVNnENcvhfRhA3jn9q0Iwnaagt8DMMWgB/SgHCJdhJvsdtL3X4mo6KmztCOq3UbHMQ9EjDcMGEpxYysur+ayTSOcLnPLl8LuMA9ClJXDknoc2VknOiMaFVf8lTarnWifh4qQdgah80xOQcQrQ3hGNkZFpuo4VS2LV2RMiUKrzoRBjsKgd+BURFwubYGKQodOFlCb/KiALVrBKPcMJ7SbN3MCOs/hbTyKr/IQu5dqnCCmCC3voiE4gGUBK/33pDIE8LcZKVmchl6QmZVQhNOSRmvzcGR/PSoiicH+RHm0MBYhiBCsqLJKiCBPPfUUwWAQSZKOEyHTMDe/jhFrjvDj16918cQIxw9RkRkqRTLQex+BDfcyUpJBD7td5zHKpnH7B2tUJh/+C8pGhW4tY7UH8VuiEuShxEjGvfYpyYPST5iOoNdJxZuDqIg1Uaf/CgBDkoDqAlGvsnnlAACsphB2g4DPUIDhmD3z4zz8S0QQBMZKKubGEK1BE/+87nSsYhQTwi+gNGAGDHz5QB4G4RDxiByN1jF5+TJchkuYTQRzWUaJ3k6eWeWqV98iy+bA7GqnMTIOISKL17c2UeDbTrIaiUlvoWr4jzi+VzEKHvLdL3CzqEff3si3212Ag4MH2jn7nldZbIekgldY9Pd9JDiMZLWkEqn/Fou0meQNsHlsBD6TxAZviNESTJKTqcPCoeGRnD4h8cR751cIOaigKCo6438Hxwf0GR99+I3C2dKp0ZGQhKulGXtMN2dCwBdixbuHu35f92khN706rYvF8+cQR6eiHqk85fk+3/wt1pZ1uKKuoT4yjj9vWseI4RcRl5lOQ2kFees/5Zy/3kFCZjcxVqRFR3hgOlPOuPek/Vat34gpO5LRv+9dLKt8cSm6TdVUJDTiKLehU2Bfuo4Bed8QZlHxdjRwXr6JQ0cH8t1rJz/PXx9/EckcxpN3XHvCvjvWb+c7f5CC+dNO2Le/rIVNa/eRfd0I5gxPOMUMaVi95rrOnz1JtFAFvK01mCMSEVBRBYGmPSuwfXcpEVKQKzIz+LL5OUKSB/1IDxdfMJeih5KZvreFqogwTEG5q9LoJ3kAOZ1CdH956Bwkc3eejqqqCIJAyd5CVn91mFCHDp1Oh8/nQ5ZlHA5HlwEiCALjavZiklVcmUO75DmOeSNUFfRtzbhLTOicCTgSwlAFgZZAOI3VSSxu+wM6UcDedAhRCSIvuAZRPGb9CZ2qpp2mzFevEeYLsvDBPxG2YAzXXnI/SlDB2dJO5Q8L2bf2By7LceMtjcHeP1fziRiPGTDadYdqdyF5PBwefwat7ADCiK/3ERmKw2hNBlTaW3cSdJvpUCfQLzUV+YiRMDGamKRmakv1pKc7UKtd2HWt2A1ga9yJjIBKBE/FfsSoajcRup/4adAkSo0WBpce4vCA4Zx7YCtpvkwGq2NZZ91PQ+67GMNa4QIRf3+VUUKn8JwOsEH10BCLWudRrk9juW8kcYYOotUWAm1QViuT0JpPMNyEI83HaTtaGRk3naClhOuyHiKU/yBnRYk8c/H/awG5/xx0BgmTVY+z2ffLjX8j6DM++vCbxODJ03G3trDh0/d5+0/XEJOWQf+xExkwfhJRySnkTk/mwNpuAqWiXQ0MHHfymPzJ6MnX1xfwXsEq9pS/iUGKRAo5GbtvF6ZDa8lHIX8DZE/RhOPKDxzpYXwoqorYu73TA2vq26leeYTbZvU/4c3c2ewlAnhtzChyhpRw1cE8hufJ+PwluP0g6Q2E+1wMk/29d34MgtAzV+M4KKr6s7qeboRC2jE63cla/Az+waj6I8TFzUVFRlVlvO1HcQcLKdn7T3JmPKmd09OB4dvb8UoiB1JngT/AxpS/kGcJsfXirdiMNububyC9zs2AutYep2joH0mDomnLIP6sIkkQ2LdiFavffVEbd9hMbr75Zp5++mkiIiK48MILUVWV+Ph4RFFk+5dfIg3PYc6br/V6Oe0//kjNX+/Gesa9WOdrOSM2wHffpZhDN4Ag0rw9H1wyw566/aTTsnbTB7g6i52cP+7k49CzNC/d2LU/WQWdrNIv7CKsU3s3Iou/OoOMyi2sLzqDlDnaYl8XZ2LX5ksYNHoUQyaOpXjtBQQdbcy74CsUWWbjB5dTbXkFo8nA7xbcwOM7V7I67jPur7qB05zDOLqsBLvs5uKsIu6Y+hdePfQIR6JXEF31CaXJDyNYJzCzcC8dQIlUx4TQQM50j8N7OIb8fh9xb6qeqMiJ3OH7DpvcQr0xEkkXImliA/4Vycy3mnk79UkszTI2n8qgCh9ztvyZVky0YsKRVkO+Pofphvv4Jr+RW9pMGBHIOiez1zn4NSM8zkJb/S97WH8r6DM++vCbxZgF5zN0xlwqDu6laMdWdi76li1ffUp4ShrlIyYx6OwYmr8qBwG273dx2OfoQcF+7AXV0+rRjI+XhkEoAOmT4HytzPBPK64CRat0CBqzkXVhLLz9Fgy622k8WsdHd11H/gZN9C0i/mdJfipdZbunwq4WN1+ubiXeYeKSsak99jmb/UQA83e6mTn6GQRbJD6/SIMhGt28P/DwhWN5/onnEYr2nfIcqgqS2PtYFHqSpx0PT5tm1Aih3vefAGMeAlBDNJIgIYgiUlQGNaXVHG4/QtHaz6m3lzCxXWaAJcSuEQ78xn24ZcirsSCqdBHGpddo867qVZruCGH7ScK8TyRn1AAaBvlZs87U7Vk4DqFAt15MyLkas/l2JEmitbWVN9/UKMCzsrK4/PLLEUMy6P+VOHzP8wTDffxkMTHrlavRiyAqEAwG0Z+kr5AeDMnR3PHWIp6/eH6X4SGIUcRZMzk3SuOskdTuxUlRFcTjRAPDDLOBLYQniXQUX4po20frkVm464ayq0Zh14/biMgaTkTaalZ8PR1FDKLPqMUt61ClEAeqt3D+tzrWztezOfxDtvnPJzwrF29dIt83p7Hts/fZl6Dxj2QEghzcdjU7zDkcJZVDDCSEgi6ijqBfQn/ExfrdI2joP52GUnhveDqfF/yZbdP/Tsbo+RzaPoHzsHCJWw/5QWZMt9FhEBgQX8yc9d3zsj2Qw8aaNBIPPMLQpAu4442r/oXv4teJiHgLzdWuX274G0Gf8dGH3zRMNhsDJ0xm4ITJhAIByg/s5YdF3xP+46fUHdeucbX2rzdYgDZHAFrLtQ0Hv4Tp90FkBihuZCmKfwx9n+tatFLN2q21JI+NJyY1nhFnXEt1QQGSQc+AsUN79KuoIP6C7gpAKtoCMys77oR90Sk21HoX89Lt1Hz1KEqwGfiE1dHTadrfzLDat3H5gijyLwm8cHLPB3Tmf5wIV522GMruf8368HgSsFhq0TV+2LVNBv7RbAGOwNEnIB5q2+KYl2FH0l3AlMmP8sSmW4BtfDL3lR7EcHsGDuHO27RqF8cNrbx7zz1E6iMR1M7x9MJgO/qseTRVtnN43adIVu07ufzyyyktLUUURTZs2IC3U2JelGVUfe9Mq0A3VfrPjJzDUck83s/EeJMZm0/rS6c7+eNWULU+BEGgsb+emKIgghhBkm8QQx35KJYkUEvRR5vZ27CXK5ddCcA1be3cfutRrQ9FM2xOv/pCTDYDakgm/5slRJ1uRMqI4PDW3TQ113DGIa2y6XBSPJXEM2r8a1Tve5tm0zKkUQqRTkgLxeMU/UTXTaHz9mNc2VD0wTOpjlnPj3V5AIz1HmIsh5AUB2nyaNS2IBLg2vUuqYk5Xdd3U9Fb7JJyeKlcJipUzDQhnDOStkO1low7sSnEulgd5XHdSbk1YdFsNMyERBgccjFCrD359/AbQHicheI9DV2hwd86+oyPPvzXQGcwkDV6HDePGMOnxRU8UVxFnEHHO0MyMInHykSPPfzUYySS3L/zDYrbVnNZTfdba0NZGbG1TjJ9WhjlwUOPQ+KfuLrUj1RUxpGVFbSdn4l02mRST5uMCmwobekRvimzguDzs6uosWub2LkACYL2ORI4WzAw+apcmupdNNY5UdEYMlVV5WhxE8MFgYY1jYCEqIvFGH4r59a9QbMhEtlrQW1uRy/IrN62EL2tW8Tu+MebKncAPUnOjkFRf/5e3w1bmpbkWlFbxrINZd1rsNBNwiaIXbJ+HN7xR2TFxy0PnENIDhJSQpRuX0VmzTPM1nVws7udd+1hpGTdgDV2EIIgcWTvNo4WB0j09mfxpg0cjZapraokITOc+qhub1K7EEFFfBKJwxM4fGArcBY/rFyLpKqE1bQRI3Zfe5IhiqNRv+dYhD0jI4OMDE0AbePG7nCHKMsohpN7ProE2H42QdnnPAIHynnxpge4/4X7tCanWFC8IQ/lHWW4O9qIKdJKT1Slley/xjFo7F2IVbvg/blIRhMlbSXd15w0suuzEgggqzr0pk4hO53E4Iu6tXGmnjOYVUu+hs70pSHVdQy5vhCAmMRX2LH4AgIjmnhjwyN8JLiYMv1W9q2RyXbPwKw2U+ALMqp6DjPrBkPMn6k3x0F0PHGV+zlX/ByMnwNQMfhm0vRV5FZHcrP5dTZGiryqRJLdOpKBZTXUtPj50/B32VXdzfr72EEfh4JOioJ66n6ncv+Ap6mJjuWLjQ3oVYnYWAdFnnpev3ktZ96cS+rgnl7E3wLC4ywEfTKejgBWx2+fbExQT/a687+Ejo4OHA4H7e3t2O0nUfvsQx/+B3DA6eHcvcWMdVj5eGg/dCcJO1y78WV2dLI5AkQE7XxW/FSPNi06J5bTh2IPqgR+qgAgJMD4OafWmohtDdEQcfJ3gE0rnZhOXqEJQEBVuSPgoV1UmePRY1dFQv5DhDzdFN3GCJnsC4+ctI99++aCMYw7bz5R5C537W4akCiZOJh3Vm3n49VVpAoGYocZCbOJJK4JYgj965oaldGHeeqxPwOw7r1HifvHZ6C3kH1+cVeb73fOpTrlD70e7zc20xFxmJG7d9O/qBivwYjXZMLm8SCqCt9ccD4F1ioml172i2MRPYdIn+Pgi7owJLON7Hgz+/YdQBUlsgYMJGnf28xq20XMoFzW2QdyIHwCx8sE64urOb81C6n1MMaUOFBUVEXV3DmdvGjbq7zU2TJI7Fz1j8+gUQB3yEf2rpfZNVjigucW8fFtfwTgQL92wl16hgdlskw+JocXAJAXO45iUxJfRk8jXCehR0WPitzUQK7nAFL1TQiSgChq/47/7Bh1IbmHO7B3CCyadg0+s72zgkckvlWjJ89Y8R4/KCF2htoYYD9IviecMe1mVDELkwoZxl2cFfEEfvtAjIIH2itxRQ3A1tx9fy1iJrvJ7THXFtVIpGKjVTVy2oxZHNzxBWe2TeaIqQKrbKagNYxyQz2HojfRHDeToE7Pn7/6ipQBN9IWcFLkqUbUp/K7eycSl/7rZjPtDa11bj57aDvn3D6CpIG98Oj8CvDvrN99no8+/NciN8zCezkZXLK/hNcrG/hz2olhDYCXx9/IyrTTOEb34GoIQHGI4mkG4lJNiMtbiGwIg8XlBI47TqfCwuTuBNPjTRsBuKSyCl+EnmUZyZqXhc7QhwqqoiIrKhdMqmK23sQVydFdHhFBABFtUdm+tZqmrQ3cftVQwiwGFEVBlFVizcNR5POQJFh8/z8IKPknXJciixDIpt+IZ9m//00ibb2HF0KqQP/yPF748EnMXjcXI+DKHgWl2v72aBg49zTGJg/srAg59t+x6+mmrP/rhr/SomsE/syWz57XDA+gbchQLs18lvGBr/DIA4iM3s9Ffx+E39eGs72RgNfD0SPtRGUmU1dmYH8pcO0fiRg7lChZRQkGUUMhVEniBoOOj/d9yjvRd/HV3K/4fNFjfK8/xMb5P2kD7nzfev/2qzBKTjxr/FTFXUWVKrCmMgikI6Kw46CTkHQZSpzITc5FLHCu5O7YOV25QABzYsIxtQNRI5HbOjhmcajICCiAgtOqqRkHuwTUOjlWUGlWo5F1evLTkygaHU9sQip3LlzMpp1L4NnXATDHSdR35qkcNmTQobPzrW0EG63ZjAjWEUQkKIjUxqTytX4qf8v3dFXjdN1PndIBvtjJHBiykRYhFsG/FotfOU4jGQhZaDcquI1Gxhx1sF8ZQ6soYBZMoMJhfYgUVfOQGTsKu+6RY4aHGzPPcgMqP2NnVQUu9U/q3rCimhuzP+eVhM9PvC+dg/n6mQfZnxJLZWQYldXPdO2LyTiTuPQzTjjmtwB7tBlBFGit9/xqjY9/B33GRx/+qzE1Moxx4Vbe3lOJ4eMyYox65l6fgzW82+1p1Rs5J7WbRbFQbgEOE5maQfbgWELJfjz7G3v0W7C/Hku9l6n9o096bqG6ijCDDre5CY+iMj2uPxICP1TnMSw8njhTOHU1NXjjrORmx/bax96KdkxyEzmDookK+7mrNhKA8KGDqTpcyqi0xZiTktDpzeTvfo/a1mcRzYdJjUlBVSXNGOkFZ1QcIvGnL/EOzCVi0Ehaf/gAfXMdwah49BIEZRgQH0lmSmqvxx8P324n1rYA6564hfDPV+LTQ/DhWxl/7o2cu24/a7gBgMdaSgGVH56tRFX0gBGIpWJbgJCkgxiIDjcQn5jco/+Pn15JZWsBxVHFhGIDRDsi+dKsyc3WthSSMWAsoijy097N/CF9AzXbw7HGBTjPcBfrlVEUD3sZgyQgCSJhFj13rMnDlzqDhZH9mFPwHgfnT+nhIdtX0ADFhbivG8zArN5DAZkv76WwoI0LX7uEVk+At78vRPbLCIpKe5OX5DIfbyxIILwzIbnd2cKW515DQiD50rlcdPafKa2r57lbryX9prs4f9pUrtt0CBsq38/sDqs8ua6Yl2UnN7x0cln5qnv0kH8tB4bYicmMIOFHzUvnk6DFJNI+IpqzT/Mwq9TDH3LNXNb0I7bR51EXHMzat7bwxwtGk6Q049wl4Rl8BbZhZ2NNnkHjY9GUbojGfhQu5CseHn8V2+KHEMoMQ+1n473WR2HXDNocYLtwMKgC2z9toU7nwz/iNpw+mWBQZefuQnRJLvb9aRo260hYrvG7pI6dQ9W+ZYw9e9JJr+3XDkknYo82/ddUvPQZH334r8f9/RLZ9mYlIaAWWPVBHmffdiIx2THInUyVYmd5qc5uxD655yLY1tiBqdF7yvMGVaj2B7kgT4vxDy1eQpbFwncd0UAVYugg6CI42NEK3bRhPXCsWkbphYWzGwqiZCE8M7trS87YGwltaafZ9yZ+twtnhwmPO0hHh5bUd6w3WRVJ2bEGGbj+jr9qOSlnaXyon/7zRVqD2lw0BBpOea3HoKoKLz3bDqwEQLhjAREt5RTecz5XykP46Mzzeea1F8nKnsXCRwoBPYIUZPZ1SThi7VQeOYgseVm6BqwRJz6kGzqqCJi6dUuU43Rmztl+PX/ePoMbfv8Sf1zSSp5PwlVtxlVtxpboo9YUzhO7KugZ5ZIoq/UQa25CFqQTQnNq5/yfKnFY6GR2U1SVv3yyj5F7XHjMIopOwC4KtMYbCZp9qG0NvPjybTTXVxGuCrgTDFx0thae0ncygMqylkjbFgyRG2bpcR69KKCqAiFZQdcLZ017aS1+VIwI5B7ugMMdXftMMiS6FRI3NSBOs+D3CtSv2MzYyA+h/EP6Af3i4KiwnLbAZkpHRQCL4chi7AeHEQoms3y2nnHf6An3Brlz12e09Mvg6JynUf0PE9ZJ/x/eDgFXkLQBUUiqi35BeOXjzfgVHSFJQifLyBVQQyVQiSLqEJUQhvi3yL44xICxvx1uj94Q8V9UbttnfPThvxoVXj/3Hq7g7OO2pWRHnvKYY5Uj4klyRABUWUU5RcK6qqoIcjug8qckM/+sM3IwlMrBzvVAUHzYBA8dRDDQ0HbSfoTOMcinSN1S5CCS0U9DzS5iEkZ1JT6G2TNo9kHB3vcYPGQdUVHV7Ny18ITjve5cDMAnN17eY7snpT/YtNi72fLLBGOgGTXLRoucsUtb4tXnf8QLKDaBK6Kruak5AV3GVbQnH2XamZo8SWK/QUQnaMZXbFIqNTWHYM0hekuDPW32CDZsdAJaBYiiqKyZ8z1HjmzjD+VP8U/WcEFjJW/NaGTYD2/xXvyzVGSls9IaS9CbQfEjc1EVlUBIYfeBOuoXl1JkaqawbRkzODHxVD0uhHLKq1ahzh8kZ7+LIwPMvHTHhB4tNr36HBN3tCH7WjGYFdx2kev/9mLXfkNnpUwoJHO4w40M7HX+bJFqqIcoC1uf/wGjJB6X/Csg6nVsO2hiuMlLnN4AVjMhsx5zShht9W6C05NoKW1j8I5mJEI4smVyp5wGi6A27jyEkEh889eYTSF+ME3gfvd1DFEPcCdP0mHcz9XG1yEA789XUW16pjnWcVXqp2S33ELU7msxy1EsF2sZrMaS+nkRlRRg8D+F2LaReL2Tcr/CgUEjGHl4V9flBKISUG2RBAURW4IWNnS2NeCIOgUfz68c4XEWSvc3/W8P4/8J+oyPPvzXYlVzB3/KqyBcLzHt6XEMtlv+pRI39Zj8+SkSQVVFRT5FX4IgYMVNuiHI37KnkWXeg6oqOIwW1jRUMzsujfFhAxmws4Jap59DLW1IikJamBWLsTu8InUuwMfLhiiKQm29m7o6F5JYj3XgO8RO9XCw4CICG/sRn3A2dU0fI6BHHw7NTWuJjGwCkokIv0Ibf2dfLW1P4b98LGbnQL5t9WAUBYKKigLoFRmvPQKPycp0Q7eq7qmgqDLvzxb5YJbAPwZdzfT+lyCarIg6M1WPriWUVA9HVcKijaSNm3HSuQPwen243e5OATYRQRAYddoQRk/K4Z1N77CzYichIUhEbDJjYn+HoegpAnr4/WdnM1U/mJdnb8U7F/wfDsBe3sYQJYTyaDw6fRDJOIbR+nBKuIqIukmsN0zjvoQA15Q1EWwPMS03FlEUu7wk/0phZKxBh0GG4QNODM/M3hAAdLijRf7+6uIT9hs7jY+GbxbycUEx5GoMrje/9g0Tx43lslEp6IsPQ9QYdpfb0IcEEE70fji9B0gzTQKfCr4AtDYTBcSnRbKuSfPUvb8zxPpciehUzZsX6j8ee3Q2fP81iAac0ijAx2Ehly/UK/g97xKY0DMseL6qhUv8kcVUTb+PvM8zCXn07BAMfJ16KXeIcSjGHOpb86gwdrAlp4XWmADjj14MiHjD9Jyz7O8AFAy4GOZq/e5aeTEzL173L8z2rxPhcRacTV7koIKk/xcYCH/F6DM++vBfh0AgwPuLl1JUWMjZiiYI9tEajVgM6LGSCKqKKeDHaTRTEpPEwdT+XHRU5o+A9b18ytUgqqpikbYQa3gBRbABArNUUARofuLky9JWFT7udzZwNhelayWT7e0N7Nv6OG95C7jb4UdMfZmdujhm7S8HQFQUHEEf8aqMGAwiNRs5G3j/hV3IsorOK2P2KRjV7vMOOK+bstkQU0pL6AUM4RD0GAm6rNjtOXiFIsLCIhk58roeY1yx5mmy4iPYnTKaI3UtAFhEEZtOxCAKeIJeWmQd5bUlTIhKRydJPYivACrqqymuLqeho5FGr/ZW9+iYGzl9yJ+72jTu2ooUsmCfNRT3uy6kHYlU7F0OKMiqQLnawWbTAQBiQk0gJLB8+SGWLz9Eb6i2VEMczP5+dvfGTsdFeXiQcvbzYucwB+ckEFY2hkIxgjF6zbDs8Bfxiv9qMO1ijJSJJS6dZTnRtGzdwln7W3EKmaTFW6lxtxGyF+EqC9DmsyDLMiE5qP1UQoTkIDUdPvxKFHtfWgOIHKlt5dOtZd3jOu4WGTvxfJZ98gFl3qP4xXCijEkICIRk7T51WcyYWhtIbG2kJiKGb7Iz+aajmQMbfeTlaLwaY7JasBuNCDodTQYDHXF6dCJ469rYvLWKkvpPOTuuZyVQzdKdjIi0UGuFNLfMtIp2vEOMWAG3uwUhWI0DCOkMZOsc0FmkXOkehWPw3GOOpi40EEcYGmGWqFNJmVJL2fJUZDXA1O3P41ETWJTg11J5AJclxKBaE6JO02qxeuHAkOvJyXsXfXgdiiwR5vXjPDyEoF/u1igSusNa3du6CQJ/bXwZEfEWVBXaGj1EJdr+t4fzH0VfqW0f/uuwdu1aNmzYgDIoB8sx3Q+tHOMEoi1v3kGEQDc1efPUuRhCKpPKFMR9GxGCPiwRkcyyaG9pnuhzEcNSqPMF2UuQ2ISeJajHPwr7H3ybI/HZTLxmJaVle9m5ZxFvNH7H0oZyLKpKQNCzeXsMeeMuJ2rBAkKiRJnHR5HbS3VQIU82k+BSOHu3hyingtMqIobpsUSbSEi2YQrdhCobkANmXMYQ2IwkmPZ2nd9sSufdvaO4NPsbVCCoWug/4isMOgt6nQWDZGHX5uGUC+cwe8diJo7VKlNKRiUSksL5x9Yy3pW0t+WoyuuRFD+qoGIKWXDIUTjUSLyChypDMWonRWqYqJBtknn3dwUsWrOML/M8vH7t6TS8vRihXUfqPfOpfWA7qi6EOqaN4CErRqcZFz5KpxxGRUXXUIlz5wFKfHFa2aoACcnxRPbvLu08UitTWbcIl66Q7dmalXHV0jTs6UbMA9NRVQUpuJK4Adr48794GUE0M9r6BaPDFlKo13NT9ECGVcUzsDaM2eEX8sep67nX+nWv99STtSbqQ72/qfZvHM3M4iu6fn9vZhjV0T1DOHPXfUtuwZ5ejz8e0bKBspxcjKqOqJISSsNEPriw24gjpHDb962Eyd132orhZrYP1O7zKdt+Yty+jRhEEwbRjE3vYFLc+Ug/I2Oz6z7Ervuqh4hhoy6cUUkfEbAZINrMz3Ft1dfMb1qPjIh3aDVCZyKMu95E0fcah0qE0UtspUpmbS3LhmV2edi2ThdowsOQmukMbpjY1adOl0fmOS929XW4YTAHDozhZekNJEGlJ/H/iYZG9/4T2/X8Sxe62gs9jjuxDb3uP9m+n+UInXQcnZ8VFUXV4Z39MknTevf8/f8ZfaW2fejDSVBbW8umTZsYP348c+fO7bHvo4/vobTEhN3uIhgUMJlM+AJaop/NZmPKlCmMHTsWgMajFRTt/4yR8TW0nLOQ6rXjSHJtxz1yPjETzycdSD/JGA4e/In2vGXEBF381N7O/a8Mp8muOfBHuCzowlKg4ygGNUiW34vFqGPciKEn9JN+zxJiAhLRHq2EM2tiPL87v1tifPWaiq7P7b6JXDL7Lc558R30YoCHZ+XT3LyWS7PLAe3RZxA8VOw7s8c5dEBkUx79vNXUrdeqKNo32bhs4BvsiUpmWrvIvLgQgulmCmoq0On0dIheanyNuIU29KqV6wbdwtj0UZj1JhrKLkDUBVn50wDKjkxmVuUw6v+2GaMhEXl0LVInm6gpI5qYs6dzoHY9RifIo8OYN+827fwVB3CUT6ZywpO4Gls4uHkblfmtTByaSv/zbwHg5XWbuPEP+XSYoSDFQGZrOs7sYTih6y196nobFVMdeBvtHB3cTrE+nGBlGUlRJvb607iuWcHjacIbdFNsOsQ5ng3QGV0S057FZkmioWk9psY3uCnzBrKjp3Hrusuo03cvMLlhCxCql/DdkHyu2zOZjLDhTNjZyuDHjs8ygsMbGlBHjifnlulsL97GrTtvAQQ2XbSti5duz3OjUDdFUKoM5Ye4oUwPtHC6uo2vV1ZzfkYHev1APj5Sx1X3TybMpMMXCPLFg7uY4DDzQlYsoWCID9a76YhJ4PIrr+4qg1YMRlqu+zP6tH6k/ul2pOW3I4cZqJ3wDJ6GPDIL3scpmrnK/VfEQhd6u55gtJl+SKQEIMVu5hOfC7NgJjFmAiIq/sqFlKfoCY84Dcq2dl2nJxjJI3ffzOniZ8zfkkxHvQ2rzsFF5QPYQ5A3DFs5Lfk+RnQkEFAtNNmhsTKZmLRKDjUN5PvSMyhT0lhun8+ktJTuCewsLRZQTpRh6iQO1ParXeXgXRu7fqg92nf9itolWtjDZFFP+HDcQb1sO8W+4+ULYhoWEibvAn59xse/gz7jow//VVi9ejVRUVHMnDnzhH2lJRp/gdNp1kpPFRcWSyxZWVnMmzcPk6mbAdRz5CcmxmirmOWbyxBEEXS/7Ob9ftVnnLPpJgKCjjpDFPvi5pNx6CC3p43ntNHnEpXYD9qOwvY3kb0uvN8uB13vMtuHHpzNXW8vZVUZDDabmD++p7x4Yv/v2HfgViRBoV/qRRj0ZhLDzVS22Rg+7B3aOw5w6NCf8fmquI9nCacVP0YMBDDgx4QPCZlPCx7t0a9DdnGaawM5++cz0leNJMjUuVJJRCu1jQWyjj/gCOSJFfgUGy0XjmQF8xD1CtIQGWdiAj/IEYgq6MRMpO/2IuWauF5WiQGaKuuIJJHMuT0JqwB01nCy5/6RgRf5+ewvV/Duoj3cmLya2CHjCMkK7yy4kBu3F/DCgcksDytB/pkXWwjqGb64gdxVP5C4VxMZrLDUMjTNRjxaxcy+N7NBUDHOeJNjtUL9c78hKSKXgM/PzuattMqw0XWID2pX9TA8AA44f4QkMMkhJsUtQFVVmqx1mAw9H71GBYJ6PSazGUUHsgSgcqi5EgEtedR/wRtsUdeyW0qlrlLH58zkc2aCAufOmMhnbxYjiCrfPbmLrOGx2MfHAFB+1I0jPIqoMCOSEoKwcPqP7fYuyKEg7X4nVQaZxau+BeskLgn+QOK6u9GL2kLsU40cVtNJCAmkKjKXf7GUJk8Z5TYtHJRtHsU7huFsjDrClc7lDG9/npS2bbTHf0viM0YSKKEqMgz3mU/w/pGt1OWspmMKlO0/k9a2BBJCJr6RHeQFhpMjvssTCR4+bq/AHzTjKjNxRfvF5NVN7hpziyme2EvuP+Ge+E3g7UNIHWW/3O5Xjj7jow//FVAUhe3bt1NcXMyCBQtOqbOhqtpi7/fbuO66S0lO7llG6//HINI8WklqQDDR4chFESRajHaSc080agBCrjbqXryaBaG1FJtTOG/YSzQYo3hwbR3X94vHt72M6p3v0paaiqeyEt+OnZgqq9HJIm0ed6992swGJg1J4W81dTx9cw6pST3dnNkpuWSnrO2xTRRB7izDcdhzOW3ierzeGvrt28Va30jGqls4L7EfSAbK3S7KPG6uGvcCNx3+gNPa92nzAwzeF4vVtAV9hIOQLGG3lTJ4Yjxh6enUlRSjbnweu9BBRygVv2IhkHEWZlMbD3TM5ogjm9PUTQieWBIC4ciCCuFGgp4gQZ3A9jgd2SE9kwFSLVAGR5bsJffi0wDwyBKX+J9gyPoqLjesR28w8oplAXXmCL74zgffacpkOeIEyv98PnJzGRP7v0BVVTZlpaMBmOr7gasmPUq56TIO3zaNxzzDyZuTzuLUl9jWeifjIzTqb2O4n7Dk4+Y/kErhjlspMmnGiluGh2vNBNVtGEQD4YIDfzCAR5ARpABDo0ZR1VKMVTGjvzYCkyOGxMjuhf8YBAWEzvLYQKibqu76tRf0aHfLGc/y1WqAbi2ds2dmMD4zjfcMpQhB2CEE2b2vGv3eaow6gUFlPr5ZV0rM2Dgm1FnJjZxC1T0bKel4B2NEPSaTlaq5l1HfcZSQJFFrauVbfyQz4lwMaXGSJxnYEZhNf1o4x5WEyd1OgdWMyXEaxtBufN4AZYZ0AAqbB5CeWI8jEIdUP54B7W+z+3EH3tfCORgdy0VOI62O7uuLiamgqj2SEkMBk9IKiXKm83b1n3nSH0OrmIeh9W0am4eSGFaHa/jdiHICyxr3Yr5kQy9/Eb8RRPeHppOzEf9W0Gd89OE3j9raWt59911CoRDjx49nxIjeOTyuvvosFi1eSFOjmWNqWvX19T2Mj4MHPyMz0F0K57ObiDSUowoiqiDgWnYpERcs6dGvqsg0v3Etsf71fMJU7hv9ACFRx0tb67GXlKN8+RIGtEU90HlmJdJBcNoU1ggSKWknJ+8qbdEe5JL4r2XGSwIoP4tDm82JfD5hAQWFD1Jd/QmT++3AYNAqMgLtrTTv240/+Y9UBHYQ795GyJLB2ZGPEVywBP3IE0mf7ANy4IxzAIhT1B4lyVvW7gPgmxl/6nFM1X2bOEYhO3u6DdGgXc+MG+dT8MAqHPv0tI/JJ+Bvptncjzw1nTwnfPWtC3ABEQwyNDGtfwKtLh8LKyQOIZO2o5HFFW+jGoewtHYOFquPGHMTP5Y+zKUBme3e0YQ5a8mo3c2j8afh10exyDuRjc0bOd/vI/uiUtTQGNKiPqK0bgGCVIPinoxFugBLmI3q2qME1a95eMSjnJd7Tq9zftent3BUrCSuf06v+0FzuwuSNk9BWUt6HWe5ltMyhqCi8mn+QhqUHQTVEAF393yOSgsnx2iipNFFc5iI2grrTdrxx0q9h/slGp1OSvL87Iqc0nWsnP4TTmC8x0tLWJDY0ADKDCE2JGygxiiTG2vgrcZhLNj7GDMJkRMQ2YNMtOUwbkuAZqmdncHhHDZ0l77qdQoRtdM7fxMJqQJHtieijBOgBI668omvHEe8osMTmY9cOxgIkJm1E2+CQrM3k9db30PyXY7LPwPXmu+AYm6jhEdCV3Owv5M2nYo5bvBJ5/JXj+j+ULi0M07060qY/XfQZ3z04TePYzLpUYYgedtWUbVrKTEOK8eroAl6N4bYIjIz7YTHhSgpzERn8NHY+Azvf+elwmUjN8KHWVdKzZgYhh5yEub347Va0IsSgqpg6GjFdmgTba4xSFP+QVVLOc6Nq8lpWU+c1MGy+gE0tsu8M/0yJFWm8Oib6NzNFMZH0pidpRkdPj+S2QwGA4KgcqvjY9pKv6f85W9BEDTaakHUjB1E+jf7uVZK5rJPmnHYNAE3R0UL9oAOnd6EAl3U7QArxQRSrb0TgomdSYeKoi1eAVcbDU8eAoxgDEOxTKBm4CiSh/aDbxfx85S9Xvv8GRfKZVuXk1RUzndfGREUBVQFQVUJtWhJvSpwY63E9slncp3bj97dzIT8VSQ31WMr2cWaS8axoWUaoNFP6y0qVlHFo6hU28J443AQFYlQZhiiK8SaPZ9RYU5hyZEzkJXjwlcGyBBEEjpuZEjlPwgPKly0/BX+EX0PAPUhO7G6DtYQjb1Rxep7h6KlrwAq1z46FFOMVlpasn4puL5mRLxm0MqKiqKq6CURVVUJqSE8QRcmxYDi7OhSrkUAxGNc+RKCKnR5PnwhrZLkL6edzqBELYfnhcN3ApAQFsOyWwfz6toifthXw+6KNnZXtPH40m76/EMPzcFs0hGUVYbd/yP7jGA8XMv58VuBYzk9HmZ4uknw/u4/l2uNn3LmqmYGOGQ+miewwqRjjKR5XvToSDbA6qTF1NcMIbYxFW/KVgoMidChhWYSor0cHZyOfYPWr58IvLqBzDL6eE8ZhY56tjb+SFZYHKNqrsJfMYkmf4BD/T6kuT7AjribebTkbeKVAoK6V1kXupdkICSKWCbfw/MR6ZzvdPJIi47XQiGEU3gvf9WI6g++dnA3gq13ZuPfAn6j314f+tCNMwdZWFLgwYKXSuxY6KCx41j5qYre0Ex00mH0jnZ8vjgSIusptcVywJPG2+u6SzV1QohkWzW5sTUMuPxqtpVX0uF1M3HAQAYkZuEq/gbX8rsILz8C5eeQDQSRKPTPotA7lQpDOJIxn+IvrsMV48USPMpRWyP6iGRUn7craQ63E1yduhwOCBecBFwVoCqImqYtgqoiojCLDi7Wr2OxdyCV/jAERUFsFnGiINm0zP1jPhEByLGWMCSsALj6xIkKaI+D6nU/IrZaoMSGnigM54okj5vX1Sx4aMf/8Xfxu/3rcewvp7z/IFRBQBU1PgoppKCGFES9yNxDeTTFJrEvKY3p3z5HowQdA/5A9sUbGMNa3pauhGJN3devN+DXvhx8AbDq22mdkYWusB2p3svTSedqJ1a650AFBL1IjltCEGxsmHeWNrZFi2G+1q4ybCT5whBgIWOLlrPdeUnXLL7494NE+dpBlPgxZyFEwoKlCxBUAwqy9v0ISncWoQDJ3lxqHt9/wny4TLX4EndgtQ0h4NeyWcud5QCsLl7NoMRBNLe3AqAqeu5YeAA10IhO5aQkdqff+0XXZ69JI8zzyzqaDpgIKAoGUQR6sqNWEYtxm4Xrr2kF1cqQo0EGL1VJyZR6iB07RQ95iauQBS966zzc/eMxrq5FkFUqkpJQzDruGGHmjvqtlKZsYqg7SHRpLC+PvxF5loGcot3cpHuZd48mo5oETEomhVH7KQQ6vLW8kHYlE1qLeJ85zP5RE2/UTboNQ3gaflTi2mvJKS2g/cE5hD++pvcJ+LUjeoD2s6moz/joQx9+zRiTZmVM6UtwX/UJ++SAk21rRqCi0N9+Bcrwa8jbN4MdwXQOtfd07erEEOXONMqdafz4QkHX9lH71/Hlzcl4QzEUpw4l0bidsNrJtHsnk/rwdeQYLPTmcH/uorNQLDpuf//7k45dedBBTeY1JF/5Qq/7D2x6iuhVT7L85tOJiBqAKsvkDc3B6TAwfuuJi92ez87CLfaezKbmmSEadJtTUCUFxdGB5QIrkYNG9t7+/6BKP1nuQEm3cMai707aZuewkfg7QsQFRbZFncb45s0gGFm57SZq7U2Eal0oUUYIKkzzGWhJNtIUpuOKdR202U28AgjOYI8+BRRURM5M0/HPP8zm9MeXcPXGx1EEiU3zz6JNdHNk0DDaoxSmNZdikjeToGzh870X8XriKqrU/WTknUOJXsEUaOdvzfkYs4eQU5FBhaOI3LDzkBWBXeUdgMicwYmIiAhI7DxUQYQnlsjsvVCfhzMksM6dQYFFz6QJrwDgFVoRqyaR//1ObPUCkwMjObB/G195w3jyyCKc1d0qykYFJkT68MkKZXIZreYGcqKG4tlbiskdzgCLgqIqeJQAE2xBLRkaUFvSWdYhAzKDBq+gPsWBsTicXcFsRrRLFGTMx1WoJS3LumcZW1SHgSIYMpSauE04h71Dc62BspCO03emkth2gNl7MwATrySFEOwKAxsPsyF2CLNjFlFGP+Ic7VTaddz1fTNvTlnGkaRhJLwxgoqsDjocDtaPCUEQHvokxM33TWIv8Mewj/hdxQpSpjVRv9vBQu/nLJzQTPz+Myh0TKZ2+ALOC/0Ds7MZY1jvejq/akRmaARxzUWQftr/9mj+Y+gzPvrw24ccACVEMG874sILCQiDMT+0DIDqgufwGVQi/HYqG77B3/wV6GFefwMTMts5Uu9lfbkW0/bJ3a+AU9I62FJpJqToaXIH2bbyDHzGo+j0EeyunIq1fiRx0WlIBkuvQwJwx+qQIn5Ziv5US7wgaaWpSmeSoiBJlE/MwHrkREMLQFAFghYfez45k7ZmaOqwoguzIYgQ9LYRKIvG315KWuo4UOLxLlWpXbq7m7BJgHDXJhIBedn11GzNBVFEECU8/ir09gbCo0aCoKNC8bNODuHQh3NMjjcz0E6kcCJN+fEQZYVQs5/VWyqxDBhP7KAFSKKASZ9CVFClHxWUVfkZEbUOKXoeu7M0zonX59lo7lyMpkR0YGsrJcnYBqgICoyJ2stmcy6fv/t3Xmy9D0PKaHQp45kiyayO+xuX0cqexsVUeQK8kfwZmxy7ueigiWhJx4xCHf8YrFV2nBaoQUn1kH1xLsVrdHQcmcjHT85DEATmvbSR/NoOnps7t6ui5ardL2GUm7GUvQhoPgerOA5TfHrXNaeUXKV92ObjLMZyFlpJN9UQxjW0HKc44xdhu/0jdFZNVjgmGMW31zxL/qBu7Z5jaLJD6MZL6D9iBkgiP7zuQ9R5Iecr2tDDKDehn2S8gspHid3VUo8EH8I6uwXBaOPApr8gnqdDD1xot1FQr6M+qo7T1Buo1qaED+TVjNv5Bv6gDqM+xMCJi4kItTPdtArFH4bF3M7tK0Ygtv2TiCIvZxTB3OfuwtH0PLqQyuBKuPf9V/lqztmcVmtjQcSLhBSB7/sNwm0IoAgyl/ijWR63m5mD1vLjikcYuuQvTLz4/VPeS79K6IxgT4aW33bFS5/x0YffPlY9BID+yzm0huupSjzIkJAXUWcmKGssjK1GJ1YvmL0mzK4AkX6ZP156KQANbdXsLs1n20+H+bBdKyLdXGZBFiSizM08OPI1hFAyg8NfJiZnBuIcA6s//Qax6NR/XhoJ6am9ByoCJxIXdEMQtXPIimZ8BHweDPll+Pr3LkQXEXMarpZS3PpyKsqiaGtQMYV7ULX0C/zOGOqVZQgBmX4RmsfjeN0SQUVjcTWCOVSHr9apXYdOh13vQfTICLXLEICVYXbe7yQasnQmk/5BkEkQdZy4THZDUlUmZEVz799nEWv5uVIvPKs/yCtVVgodezHGzOWqn74lpqmJ5TMzyKmJpig2mXNa44nK+I5WBMJSdvJxlZkvdUGgkrDVqdQp73DhkL9SMuxlQnF7GIlEW6ONFr1IbMDAPXVX8W5rKmes+hZjQAaaiNK/z+GcoYgmle2qle0LFyIEZCbo4hAEgY93rKCyrR0VC/cvWcez587SvkOdEUExwoSbUSfeyqdP38QZ0g7m1u5gTWICB7wwsPPafPHlJF97PqFQiJKiPKK+DfKwqZGVGSv5NP/irjkQjQ0snPYtgVCA+HDNNb/lmmSayiq55ay/4At5uWX/m5y+XWHkM5/jpFO6fvxtdOgFvtxzBXrRyfCmHdjTSkhhNQVHp3f13ySo2K3RBCu3k9HUAW9B3ZxrWRJ9iLu21JFV3oaS+i25w6/Fp8LhKIVxzZAvZDCcIgq3aKGs93KGkRZVTuaZf+vq2/OhRF5dDI6mFwi5++FpG83vzo7l/vw87nvzadaMH8UZw15jYv0uLIVFRLoMbDxaS3jco4z7KIGaV4P0D3+axrZu5t7fHCLTobXP+DgpnnrqKe69915uvfVWXnzxRQBuvPFGVq1aRU1NDTabjYkTJ/L0008zaNCgU3fWhz78h6CkzKK8OMRHxhFMHvYxALr3biI18iziGAuuI3SYqkgKnolEf0yFP9AcHc+B7VXkjksmNjyJ5vwd2PetZHJ4I9WGOKIDzYwZMoybLz8Xs+OKrkqFYxB60dX4OQTh1IZFV7tTGCiCqHkRVDnU9eabDDTF9P5gTp9zD+loSZVli3+HTQlw/Ws/dO2XQzIvX/l78lpXMOKv5xLfL+WEPgq3RfPqB98x4/JYvLTw4yot9h4TXkL6wC24o64hoMr4nRVQvoMHhl3MhcO1xWfJyumoXv8Jff78ei0mQ6+GB0A0/YEaBCHA2fs3MfrAbjLKynAmxYDgZkGVnwmhIfxQcjWmiDI+tu2iRNcdhmnTReGzzuaLxgZGxGmsoqZKGza5leLw9QxyTibfUcO7I0/ngi8X4r7oQhJOmwTvvI3V6+buf/wDV3U1pVu3svhwCVmKxgmy4q0K/uoWGHbwKRbwCPfO7iDKZkcRdAgmB8y9DwFIyZlMVMFqgkGRudtrmKMKVAOKvoWY84dj6lSrHTAsl+Zvd+NJspK88xIWCDqKHQKpSfvYAwxO699jXmpTJfbHmDCfeR1m4KZkHTemvcb95hmkR40FWSbw0W5MajyzQ8MRRYEmRYc5eR3nWxaxsW4CvoDm3VviW0wYPnRWJ/KEYfzzynuwuzpI7sim1tKAuzTAU2teZ2tYCkvHDcLQnsCuqHuZVh3OlqZM5sbeQqLYxKO77uKdObf1GOe6KakUtGUBm9FZSxF0Tlwdd/JgdgKfejcwtmk34k4XsiEZZ/ZozO0xhCsbu46fuaEJn6GD1HPWQl3v9Pq/ehgd0Fzyvz2K/yj+j42PnTt38uabb5Kb25P8Z9SoUVx22WWkpqbS0tLCQw89xJw5cygrK0OSeidL6kMf/pNo8d6M7KwHY2HXNl3tBFpL4wAwchcxaGWuAF5uI7sOGr4vpTJZxyevvoG+ZBee5KF89OyjlK/fybevP8IV0y/HEtl72MSDl422PL7dshMBTfhMRBM/EwURAYEacwdJTQprPnizk5xMI5MSOkXSdLKLsSoYq3ZTv/xzerIrap9NtdpDWZEDPc6vBnr+3hsaA1pVwpbyjbz/3sOM6DeexLh07OkJtJW0UZlX2qvxcQwKSpfhccn559HmXcemhu18cOCLHu1i7d2LZHxxC5aOAHVPPsUJXp9OlkmDHGR5XgPC0u+1uRIEBEFEUGSCjV62eCIYIxQQ6W8h2XiA1jHR7B89rKt6KVZxUGANYmwHX1sqZm8kiO3cVnkJj3oG0JJWyoDWSIyYSXpUIPHMFuwurXz6D81PcwEj2dVuIyTpEFUVVJmkObMxbNuK3qMpydqSksi94ALWBxfjKtiLqqpMrjuCM2kOaqfhWXJ4P1HjJoOqdqkPA+g7Q0OtUhTF2TczZtQseKsNW5IBR0o3k21ddRV6oLDmCKYJqQzcmMALD03lvq+3oHedaJj5ZD+m42jSx+Vew4SD7/K4ZzWvZ/TntDF/YsdXYQiCkfpyGS39di57Vw3jQvOXvBD7Lq+KpzNo737M/VIIYSMUHg1ezTvYYbOTZ7NTVG8nQVdDUdYFdMScxvyjVYQdOcj9F+2kJC2NS53T+L4wE8hkQUQTM9Y3dRWWZfk+4iqs/A0dl9oPMCnfxLmbnKyP/p6ItHMZHVfK6Eho93qpRitxt3oH8bLjKiISd5P9xFHYDyYhAG/8dvMhAC3v4zdcbvt/pO3icrkYOXIkr732Go899hjDhw/v8nz8HAcOHGDYsGEUFxeTmZn5i333abv04X8awVoXdS/uoXHtfdRG28koLSNs/qsIkh415Cb5H3NPOGbbEyuwtQZYXvUWAcmIfcI8rrv+MswmI2XrdvDt649w4fTZRMXHIEg6kPQg6bTPOh2vHvyaD+xbTjmuq5b2Hho5HmckHWWwveKUbUJA8YVLiYpK5LOHbidjXwt1kfFEXnQ1itJZf9FdeMGxSs+axW9qiaUCiL08BSJmz+Sa624/YXvB1nxWf1jLzCvj+GLFVyDL/P3hh/lx82M8X7GQVlnkr0PO5q6O80EQGGO38t2ILHSi0GteQm94aNzVbE8Y0uu+gcJRfjLe02ObFyMbhkQjFNj4TLiYnINrKBo8lTSvEVWU0RucSPk7iJnVzDMGF4Pqx3PHN7WkRBwhfPRINBJtCy75dPziFs6Vx3ON5VMGL63HZdTTPiSHSr2eYHg06qAc1M7KJLEoj4AqsdU2iWBHG78r/pyt2Yc5lOTALMcxMXQQahZQqSTzz4hvUJGQnW3ESK04jSmdYTMTwZYHOr+gKgRBC8m55UisWPjUuJHhoXQKmuNISLOz3r+cxLIDmAJ+xHFpiJKEKOnYXL+V2LBWrsjU8kVUFBRTMRVKO1VHx5MbfQaHNgrIOg8DxiSgOJ3klVRjdaWjky2cH/lXJk9+nrOXfEJYWCQ2q5mAy0tuQQmfnpbMpiHDAdAdakV1RiAGotmr/46O0O8JsY7yyG1sSOmP9fviru9FNGTzp4wP0Yuatyvd9ym3YSYjEGSvfVtXu+TkQ2Rk7GHM3jYEr5Fl+Zn4vQb2Zk3hs3nnIKgqO1e4iNI/gFnaizrlrk4Vlt8omovh8LdwVwlYo/+3R/Mv4z+u7XLzzTdz5plnMmvWLB577LGTtnO73bz//vtkZGSQknLyN6g+9OE/CX2CDVNmODHKI0S5G5Byk7r2qSFP11tpYXkL1aVNGL9dS5ptMAfFozhmXMiCc88kPjay6xidV/OgWCqexFLnpTdYwu2Eyw6WX7EdRVFQUJBVWTMGVBlFVfhs6fUA3PDaB52LmYIqK+Q9fylbK6xkp5lY3/4U3sw6ss8/Xeu4x1uQwKbD27nvyHOce7Sa+iOV/Oi4HqZ27s5TOBXSE+cyq3EDFkFElZ1d24fedS1Pb3ycmSd5dgT92kIih4IMr6vB19rOqisup/SKTFrlTnKwjPPhgDbWnR1uFu5YymXjz2Td5BfQhTwoooHZV/YneUDnSd4/nTd0HbzjuxSfcwwBSc8fEmq56cpzUBUZRVEJlu1HWHI9qlezlHZm3MaSMoGHeAEPZrYevpC5W35kWOxKYkc3Y9q3g6b+QzCoOhw5Tez1DMK1uYrA/HkcOWokcVI4qs5MW6jnIhYjVPNx2OOUFKewLzUWvawQbK7BBEiudprs4RwTAguIVuoDVhqcfiTRwquDZmFKy0dS/eglP2uNZoyp2xnmMeE4VExQL9JmNdIo6DDKrSiqgirLKMpGgv5UDIIRBRAEIwaTB7OwgwXC95jkZ/nAFGBKlYsUXTZ633YA/LvKCOlUREVljD8CKRoGu7UwWvFAK00OI9FAlsGEY3cEW8K3oQpB9hSUaJdghoC5CbMrhcv7v4LTZOKT8//IzJ9Ws9k1CNUoYj93CVCAo3GVNkFxQJyOpECAyqMX4QB0TCPuvc8IO70/UdO9CK06PNVXsl6KZoEhi/7htZRWRzHA1Mw2YwvR/k3MppWtjMKFFUWRQBDYOTKCyNd0DD3UzIX36lCEZcA5DG3T7uVmaRDr4xOZPfR6YmPiTnl//6pRd0gzPpp/XcbHv4N/2/j44osv2LNnDzt37jxpm9dee42//vWvuN1uBg4cyMqVKzEYDL229fv9+P3dMeCOjo5/d0h96MMvwjomHn9pO+0paUS2d1NTlyQlcuDj/RjbA2RX+RgAdBji2NO6mhEXZTNUFAjlraYqD40UCpHag52U5dMfgAnngxJClYMQkkEOoIZCsOUB9O4SrHrryceU2J9Gq43NmzZx+tnnaBsVmeI6lSRzO2c89SNv3bwcndmMJT6x1z7k8hSayu/m7fLODUKQb27MIU1vR6fXIeok/F6ZokNNuFtbaA51gF2rDnl1YyKr4i/iudmxbPziU2R/Jc44HXNGn8vTe95mb2M1e/IbGZkd0+OcHY0NgI62+hoGruuOxR8ZHwd2WHveT0RbYniu8PdsCh+JQQ0yOUYCzsSurKLNqHGGpE/qj9hJrFVtHUGbsAE5cj2BYo1+/FCTFUdE94M32FqLXmjHHdIMwSVlmgHwEJp3RmfwsCcxjqz0KiyjPPwUM5+7xYk0R95PRTn0r9DCHTd8+SVfJpxHhSmOhJCHOm8pPknh29hYzvOECJOa2BWcQXNSGLai/aRcfguDJo1h0S3X4LKH8+yd3d6g65ceYvvGCsof04zDQ3XlXPLTP7lx0MMMiR7Enzefi9/YAb6dVG3Sxp1349UsuPk2QqEg33zwHi6nk/bCQ8zINTLmNo1M7OtbbqFwpI4Pw8/l5cOHKSrOY6stnZcenkKsw8zq9wX2LX+fqefdzoTzNEr/R247D8mahvXBzQC48p+G2re0gerD6ffEdNRHNpIckcCUmbP54eOXcZvDAfDaKrkmeyJKeC1/qYlgM1qOnhDomTs01TGWHY37MPtU3ql+Q7tlAx5a1/6dgNlCSpMTMVImMrmDtsomMrNaiTeJtFfX45YEVjgGU9l+CyG/iCip/BRZz2ExB2N9KqGDjcheHfnTKjn/jwHGtcB2t4czP/uCP8ROY3mUnvtH/wFUhWu+eo7LB2UxeMYNvf5d/OoR2U/72VICqeP+d8fyH8K/ZXxUVlZy6623snLlyh4iWz/HZZddxuzZs6mtreXZZ5/lwgsvZPPmzb0e8+STT/Lwww//+yPvQx/+DRgGRxIQwOQKsXdUJJZIE2pQQShoJa7CjS2gUJRpo99kiWUPPg1A0Zu7Tt1nVBI1soMDVe1MG5iASa/lNAnAKrmVRunUbuHMeUvpL4VoatzEM5e9T8bvz+KCOdcTQk9aVqaW+4HaJbLZG/bu0Iz1a8eFM3lYJEn2CPpHd9Ndy7KH7YvLyc47ZtSbmUTnZ8lAf28R6z58DxmVkhQPrUk2sp54HKMwiLa6kZx3dDuvzh/KmZO6Q0T2mHjcxnw2bt/DMW3WkF4PkXYIgVUfAZKeywaP4LKgB6KyYOiFAIQF9xBbv4nZi7td7gBc/hyXnTEO/8RhBAQn8617mPxwN7cFioL+s2kAqPaBwFau4Bs+5vyuJje6P+ELfy5bquPo/72Be1d8BnyGLtpBhF6HQ2khKIlURDuYNCKKluWfs1Ou6vImZdXDB45hRI38M6fn9MOzpxyK9qO4OrDlHUQymtH9zNUfCCmdRqmGY8KCqgqlLfUo/mhEYxOHzI1dbWoP7Wf1j98hSTqKG7RkVVIH0Hxc6Our+ETWR2sGzVXD7mFYkZZbU7avmCqDhCNrALLJwcbv38CRZkfS6dC5JZTjbN3Tsu+mPukCKl7eTEi1oXbG3qpaa/ns64+g0/A4Bl2Rh71mlUSzSqylnvxQHEqsBY/+SizBjwBY374DDJDsjadD8PKTfh/xnmwW/vEGtmWN4vbCZi7bo71o/mFwPXsiO41m+3BApb+9jBWfDSZlTxsAhXcEqTAd5o+52t/aextjmdRPezk4TRfHqvy/sDpKYPWkcL69+w8w+gOu//wFwjtaWbY+j0BtPcMve4DfHAwWCEuEltL/7ZH8x/BvGR+7d++moaGBkSO7SYdkWWbDhg288sor+P1+JEnC4XDgcDjo378/48ePJyIigu+++45LLrnkhD7vvfde7rjjjq7fOzo6+kI0ffgfh86oY/5UKx16gfIZg5GOhS9O726TDbiczdzUfxt52VfTL3d+174uyW1FhoJFGA5+QpjtT9zy3UHWFjYyY1As7101pqu9R+1JctUbREl7yEbHHKXOkMWhpUu4YM71IIpdkt8C6inJvAK7tvJn32YE7wimndtTfXbZmmz+wd+4os5HMgMI61w4P7C7iTx/LD5PEFuwP2G2c/jmmUepj66iJLKcBHeAOxeGUztgDqmFq+jY9SaXXx6PHgMqKhW+IqZETARZT/HDf+esCy9GEASe+/4qaD9O2XfKXSdes6yi9GKUJUVFUXzfs1xRXc3A+hvxJFzaRY4VKDpMcMkzWAFP2Gz8UVfhLLyOhKkWLizax3J3NA1Vu/moUXsubRvSyKRv9Pj1OlS9AZM7SBqg87YDMLimGQ5oOSP+5BiqorrjSyPb99Oy5Qh/LzyTsJCTs4C2tYv40t0GQIyznI8XLUIJBggGAjSXK4iqo/v6Oi9NUVVeyP8DYmdeaLZ1OOZP/0R+3kGc27aw7VA3HXpuWjIHKqpwRHQTZsVNmNb1+etdd9F+2r3sKNzAsrXHeZwztETeLxd1agklDSG8torlC8YTclgxjhjOzNueoVTch8VrQBCETnl4iWEDTsNdrtBU50YXtCEgMNbrZqJg4GbczI7djT1KE2/zFP0Bp/cpEEKIxhpGiB/SP3gaP/r2ItTto0J/mG1Zmjdoc1wTl5UnUmsS2DUkC1SVcK9CSAKXUaKQHKLzPF2X4G/UcVF8IlCCrWEEsywHCDSlUZ3o5+/C40i0kaRr55p3P8Uc8LPpuQ/wDTiXb92f4xXNrPpxO8Pn14C9d8/grxqR/X7TFS//lvExc+ZMDh482GPb1VdfzaBBg7j77rt7rWbRYtlqj9DK8TAajRiNvZfU9aEP/5N4dEQGf8yroNIXIN3c+z0n6gxYdEGU1CFEDp1CSaOLwjon83ITutqEvMXoCgJ4m6v5/aBICvIa6W804m+q0mRjBYEFYhILgwW42hs736w1ki0BoWtx3rclk0RrK47kiTilUvpPmorb7UZVBZCDyJ5WFEFFltWut9Yusq9OhMnaW6bFGElDm6a+esxUafRG0hzojxiqRkZFf2E8wS/riW03MHhgeo/r3plVRUlCDQBR3lgeuGYfcBe/3/k4kfUdtMutKMgICITptcVqwvyJzB3bTbtukzTN+lMZS2oQQujwOV2d1yN0eR6S58xFFAWCTzyK4CxE8XYgSDrcj8wiIlNbsPRn3Y17XTWyGodh/BgGnz6PgbLM4r/XUd3qZEb8Jcwsd9MUegEMJkbs7l6sQ7LM5u8X4W9tR/B5SX7lJZyWAL4EEz6Pi/B27XEY6fdyft1PjJh0AYcboK3T8DAGQ/j0OnyfvImKQFCnw2rLxWjvrlA5JvAXUmT+PuHvPLL1ESyqBZ2gI33UaNJHjaYuBBUVFWQmJ5EcH8eYcRPpePVubDs20qQUsFWXwLikQTy1cR56AdpI4TNFxac3cMP5l6OqKrKsoMgyXncTOh3IcojFS5YRFpBRTQYyd9bAzhoWHa5gVMytHJnWhoBAR8hCZtNoauoFXOl1pMTH0FopMvfcfiRNT+H7N3czodqPFL6965r0gRjSzW34JahypSKZREwS+Bxewmq6c4UA3sm7hwAfMX+qrev7dRnBEAoCEneoT2L2dVdizd+ehctqYUDa/QSEEK/2v5N/JFZyqbQQ7BCca+XP3sdJjJpLWNZNACyO3sVnGXp81RcwJnQEDiyESScmRv/qEdUPag/8b4/iP4Z/y/gICwsjJ6cnUbTVaiUqKoqcnBxKS0tZuHAhc+bMISYmhqqqKp566inMZjPz5s07Sa996MP/G/gULX4RZzg5w6YkaX8Sqqp5JWY+p8mzv3H5SE7P0QyQosNHyAa+eP1TWgIWLgA4Cq9837OvCfYEJuhnnPRc0xqj4WAcNZRgBuq+Ws0bX60GdBgb9iH9I50n7Z9BeTjCvUsR0XRaBLTqFBHQJ2UQJ1r5wvAYkS8+1KP/K4Er1Lm0BO+hQphI3MgBHF5WiNIhnzAWvy1IijeSR6c+z37vHl44uE+71qidxJxmZNElX3W1XbxuMbuqduH3h3r0Mcg2iPUt61E4eZzo+ps6aeJ3FZ+0zQMNn0EDcHtn2Mv6KUKdrOmzPNcCghVZaSJw48XoRQlJ0PHB/CuonLWAZ0MqggqLl2uhpT1DRyAKMnopACJE0TmBnYmxwrBwbrr5OT556n6C7a3Iw+KxN0Wi1paSUxlLTsbdXeNadPQ1kJ1Yx8wibvg4JEHkp1XFeFUzK/ZtAW8H8pHNKCEba0q/5CZ1ME9lXMATR75DrS7m8JtvgiDirtWMvJrKKvqbzBxc9B1X8g1irApHdzEfWJ0Uxb25sTS3Z7Eq/TFEuY0wYy0t+x7FIBiIDYvlrOyziElKRJAEFBR0P7YiREUx67XXaaopYc8TfyW7JhY5WmVI0hCC3iCb037AFq7HrETgKE2jFZU4nUBD6AhpRBI55BIKh4BQqXGNKCEboixR6dUTQDN0E5vjMbcd6FEhtW3J2aTb2gCoF8q4ZFc7n4+eDEBIkjAEAwytLmIIR3jvztMoLhxAkZLBaGEPNTkZtFas4TrfTL4/8jIcgbda3mJNVBzf2idg8ETgV48CsNrr5t2Y99ADelcWwwOVEPqNckhF9oPD3/9my23/RxlOTSYTGzdu5MUXX6S1tZW4uDimTJnCli1biI397Qrk9OHXgf4WLeeowO1jhL132nOpkzFUVbQFOiXSTGWLt6tUFcCRmg1VMHz8MKwJWYBWqaLJxyqAyqZFaxA6dDwUpoUaj3kANaioqBxxrUQ2mYm/+k+osowaCqGGQug9zbhjdWzSybAIIowSlw1IRFZVZFVFUVRCqoqiQnFrOVsaUqhWo4kUer6FHsq5gyEHXwFzE/ZLc3hs3SMsTP6KOXWjeMQ7B6u5m6Nk1vYOpu5xw4uXM0aEm4YIRDkht/xrAPIfziYoQfDZewhP0krmTRYTqqp2eWLETn4L5RRJKsagD7/exNP+lu6Natf/UFVwI2CO8jNhuIyqKCg+L77KJhSblneSX9yEK5TKoKEzcUSEIYeChDoTVz06gbsFCy9fdCNj9+/AkT0Cv6eMDMtKTeetc2hlbokBGxUmflVB/VenM8JmZkdmItL+OtzUURd5YhVTBOG0CT6+qbRQ03Rs/OEA3PBFa+fv4zHGNlERtYl7Sju9xHqY6KxA/PhFAGYCe0aMoGjgAJYXF2PFw4Sfc54IAtE6lTViBZPamtmpz8fgWUeREkVQCOL2uvm66eseh5wbuh2vK523bu8s8dbfSXka0B6CV8vxi/l4xzn5PkajJI+1pOHVO3GaWhAbBYTPBBDMREgqQ0whDjqj0DXNZJS+jDRfCzR6Sa8opylWCymGRAWxU7ZQFFQUNIN4TYdAVusQ7jraSnGCHlNLgLa6bUw/upNYl4R1QTLDbB5GWreyJnYFTQjsjk7nuqqZXddiKirkxg1rWXf6QBps4YxQtcRjl99Adt0EXMZWXIl1zKhdQok3k18mcfgVIjIT/B3gbgJbzC+3/5Xh/9r4WLduXdfnxMREli5d+n/bZR/68B9BuE4LCzYHgoQUmX/kb6It4Oa+wVMJN2qZepIocaQjGufan9hzqJCXbQKKFUzb1pO3XUWSdISajyK7HaSccxbRw2f2eq7afXUcKDzE+efdd9LxLPv8MO7wCC6YNvWkbVi0hHDRT2aoEsGgZ+6CyZitWrWKHApx7xdV0ACf9LuSyTEqshIk4Gnld/lvkJ7/OoIQQPEpBN8+xIbMdWCAFfG7MT51N3NmXc3YMcOwmAwMqjPRHiviu2IeqqoySNGMqVpVRVUU1GCQpDeX8Pbqp9k30M5MTmfLoi1sWbQZOkNJVoMMiTDvs7k9QkOqCi4dBCUBNeIawoRIfn/6OSe95JcWryE0JoPsc3p/o5W/3cyeFX7GXXUx0cnaQ3lJaytjdxUT0ulxOYvZmZPN7qGDmHJoP9ZwB7Fjug2isI4gMXYFz0CB5h+tmK69ksCbH5GgNqJceSlhejtpmHjztS+5tHAV+qzZHBgyhh2SjW9TrwPg8hEmpmQ4eH59MW1ePx9eMxa1pRD7N7fjGnQRceMWYdDpQZQIPDESSUxC2rxcM6ZUlWRFwaDToaoq3oZK+OrNrvGF0NHYkEaBUwBDA8Wqitm5AgCbXI9HEBgkmIm3DSM9ejRGnQMRkfatWt7DxFyvlqOkapOvhKwY4hNxyy7el6G/cRAj0nKRVVkr+w7IWFoMfOH6BhBokgXi9QomQxuifQfx3vFIJhFzhMDsNB07q4fSEWwmydIfQQBD+Bf4Uxy01M/H7bfS7u0AQxKmoMqmpJsgCaKjYwkrD9CuNyHKMookIbvtzApE8oWhlZkRLgqyr0IQoHJ9As1xkSQmG5luPoqn6RqWAjfEncdwy2Xs88US0PlIDEGVeyzBtqbfpvER1XlVLaV9xkcf+vBrRqReR6QcYP/Nl7EfMKJRFrzLa7jDwhEUBUFVMHuygQC6wgIUVUDplcwol/ntQU5WgX8sWfJUkBQZWTr1n2Csr40ywrk9HyDI82zivEtmA/DIg3fwpawRpKk6ibPOvFX7rCisW58JrgbqtlVTIY+jHT+nB/7Ax7pnMAREzCVV7C54mKp2N2OaIM7VjG9gFuOvf4hQm5PaR39AlcPQJyjE/nEugqhS+OYSzjBEMy5xCLKtnaGFW6kkiY7McwiFQkTX6Lim/hyEDAuivjv/y1/URr5dRB4UwSp/PKI+8ueX2QOqcOq8kS6V1uPcUYkREYR0WjhNMRgxCzpCHjdRiWmElGTgSwCCsgWnXcsfEb0CxtQBTL7kTlZ8+DmRopnTz7q1cxAqL+5tp9YeTeWk/hzIGsTp9QXQGYIfZb8DyeXi8kGxHG7OZWDy71Fj0wjp27DU/YQ94omucYqySMhsxBx1ogKrHAiw+53X2ZY/iYlDksmvqeFo/CgogETJSXbTFu5/aRbvPHg3L/WDCr2OBBmK8LLDtYfk1u1ckTKbfXU7CTPfQqQ3HvuMgZRs2IwxbASTL8zR8owkAbffDV/AGeHncP2Ey3qM4/o1r4ILwtQh5ByqZWBlGL8XqlgxdBBPCM+DBPmWLBIf3s2oezbSEWhie8tiovTJuK03kFbRHx8gASNtxWysf56c2O6Q42sf1HR9jji8C29CFCGzg8jqsbw45TvgKO6gmcOHBmIuc9Nij+Di827jipXNGDv//ir8owmoBobXziAoBrgu7mKuCj3ApLp6ppzyjvqVIiJD+/kbLbftMz768F+DKIOOpcMz+aaXfeYxkxBFEUEUkfR6LjhzPklR2iKpqipyKMTaNdmoioC32UTxojSCnDx3RBDEX5CMA4suEt8vLMSP7nmPtnGTcGUM49GjRgYNTu/alxLtgHrtc4eh2wwSRJFp0zX+g3vDCvlxdzXuVh/lN1/IHWglr67LfezZe4iSj7/BOnwebfmf05qmUnTjUGIsA0G6HlHXiNyaRsvnG4j8nVbJMylqCPYzXweg7olhJBrqib/iCgCW/7CL321N50CrzMBLs8kcGofLF6Rk73ZykhycMXUowzcfwq+cemZUgVOWF4udXhVF1kJjhUePcsGefOJMEm1Y+cvk8SxbsxODKHDvDZoY25Klb2IyVSPiZ2zuZppKf8T3/gtE/eGsLkMn8VB990kEgSnD6vkmo5A7kzNJrr2GDANMHr+JNHsV5rjnKS1/kwRrIQ6DxqshGCy4p1xH+Jq3aFlyKZHzv+jRX29Y/9Df2FuSDwiUtEu0tKoI0UEEOURceTFTI/rhfO9R5u6SGb/Iz5DdhQiCQDDg4f2l1/Npy16erFsHQErad5xZcBM/PvYqp+9ajiLABxteYbbDgGVMHMrp2r22272N69GMjz8++AgHEjbTYapDlEYwxTeemErNe/1DCmxKXsVdrihubm0nm2JW3XsjdRF7CVumoz06nBapnlliz7dyER0pWeewTVfNeWXnsT9mDz+NrWLuDh/m8X8idaCH/SXrsDa1UZI6laSgCYvexwOb78Pe4eRMw0ZM9kjm7d7OVxPGMTZfIrMmxE9tdyHZK8ALZ9lfoljuxx51AO9feu4p76dfLY6V2/5GK176jI8+/FchPTqKOxcuxtPRzhcP/pWopBTO/sv9pzxGEAR0ej0TJi1j+/bTkUzaonds8ev1GFHoVK3thqqoVO0sgZZGdPmVpGdeQQKn1mBJbaghYe1STFdcDp8d4fDeIwweppVYXnf7o2QeKubqTwrJzuxd5+LJaQNpcPpZva2qa1swKLP9xd2YfQo50WcQMNbScmU+asRRXK0Bsg6uhGE3En7u5VTdsxF/qZXqB1ZgGn09SvMWAu42al46nfRAOaVDutVKC+MkDuLnEtUInx4hXzqCQYUwFbJPSz7ldfaYJwSUUxgoxzT7FFnBFwqhe2cJB0WtdHbVmMewWifgk0MYgt3lzmPHvM3O9cvYW1jHxKEmEuPPopQX8O7dypa94aSUa5VCrvYmbA7NkLO1RmEIHuSfxQe5PdZHmlEBnKjqNCYOOZuJQ85m9ZpMLPru/JDwKc/Q2lhA5O5lONXLCJv/iSYFzPFhKC3/p2n/XqxWrSpEEATqq44iALai/ccaEtx2mKo1exBEleQxHV3hLEHxcNnwy7g+9SOCARd6o529r5/FVkCwn4EirMCv1zHHoSWJenfWY52heV6idN3GQqNpM+1mzStx3ZJdFKanEQMMqa7kg3kKggpbcLDfHMXDVR2UD/WwMXQR88M3k9jWRCjTjjR+GUeCr+NYOIzo6BuIt6QTL8NEeaBW2ls5i7wBbtrnhgg76CCxtpRip0CTw88Zl2bz7vo/UdOkkOoTudWUTLz5ckRE7E4zswrhyklhPLBQy7HZlDCQVWdYWNP6O17a/zg7bhtKWFz6v3Zj/RoRlfmb5froMz768F8Ji91BQuYAGivKeiRNngxlbg9PPfo2NvdswlSZMGq5u7CS1palXRoTxzRTBMA3YCxRUSms++R7DIqCTg7iba8nl2pMvhCTOyYSvewvqP4OvqufhCpKqKJ43D8JVRLJBfQuF60P3g0Dr+WuAlj47KJOsTUBt6KdW1YUZFnG6/Vis9l6jF0n9lTPba9xMdCpuRYOxxjxDHqGkFl7uLdEGHCqDsLP1UI7lmFBAlVtyHoDom0M4qA4WvYuIT2QT74+l0Hz/9LVrywKPDclnDc21HMDRsx2I5mZkaQPiWFIWgQA4+qDzCjzsXLvDkBLS+gx8ypcYCvGtP85Ggp9XR4DtWtmBeIDASZHq3z+yWR0IQMRosBi9VpaBTvJ6/TMd+6mJTKSdpOVc37qZmANSDm4+vWjYFMeB1obyZhxDVccXMrUjAfYHg/96uDI5Cnk7NiFwWRhQGo6lMB50pUk6d4GTzLT5yxGNHQn6hoMsQQCDT3me227g9wMC1l7FlPXMoWIUBA1oBlCG195gR0bVxOhCLQeVy6iqipZY8ZTs2cDEQYv572yFCHkRQz4UAN+hDUPIpUu4f31z3DR+mewKP6uh3de2vUMv/pZappGA+DqZyf+gZVUb66CXRrFgWlQJGabNu79zaWct/BOOvw+WuKauseda2asksfQERV8NSacq5Z285cAbCEOZ7vCkelZ7Bzj54zWZUxJqmCr14lqkvAM3cHRlclkDNX4cUImD/7cKNAJxCcYcXzjpTSqFvdkEatrLB96v2JWMMTr55/HkedXEqWPwYmfKmsLlUIVc5zjSPdoluauTCOjS/wcTtWMqaGuIyQLTdTlHYL4dH6ziMyA2v3/26P4j6DP+OjDfy3SB/Yjb+Na3r1mAVH2ztLLXvI7BAGcssSABj9BnR5fzkjqo+KxxSdi1uk7izW0ChZF7WS3tNnZH5/CjJoKgoBbVgkZwrFkbmW0fgemldNQ/Vo5qN7tRlRkLedEVhAVGVFREBQFRRBoDQ9HDPg5o2EfhxL60+DSaYU1qAQBOdKB68BWHl2isVDeeeedhIV1L5CiKBxveyB0knzVjoxi7oWDee3dOxhu/5Qyf4jQ0Rj8MVM5VhgfeYkWt1dDIarv34pkteIt+IEgOvrdvrRHbosCYNZx4OFZWE/C3TO7LsTgNpmqOF3X3P4cIv0xE41b1wp0TqiWPYkAmKQOcoUiNjMcny4CZ9BGq14jCiszq+yM62SaVU3U+t3dHRuNiKKRgwYj9VFp1GelMbqxjMETZpFkjQaaMAdU5r01DZdVT6s1gfbUj/kwFOIraQSqRUDdvEfzzCCgIuBRX2EcW5FXDkAQtCRdRzockR0c9GRxdtlBxDAVV0EFxUNz2TE4FaCH4aEIIgvnX4M/zIE9oT8vVL2I8GouekEEURMtLAhKfJx1Cx95Erla0QyKFdHTUWLLKCCf1/7xMklNw4gGdB1B3npDe1s26LSZC5S2oD6yDUuqnRppP1HtYFBFUvwKeAz4JJEx++OJ6deINNvD2UVWujWguxHhi+S9x+/hT3+KYHhDJKsKPDjzk+gwGIiQ/EhJeRypOEh6yl8I+I20bXIjipCoEykyVfFP6+cYW5vxizKqAGvefwU9xfRzaDkNVlHAEoohRU2iRfUTUF3YG99lc5rIlsxIAtYJDGgooKVjFTcPTeBM163Ef/N3gm0BEjriEQWh8y7pNmrV4/+mT7jhftb2uP3Cz4/9OX7WV09fXe/n6b3tz/vq/uzwlGHz1yMpyr+UR/ZrQp/x0Yf/WmTkP88gux+/rENQo1E7GSCB454OmnqpCZWi9GwmTc3h8nm//8W+V150Gcn795yw/cAF2bSmTaGg1crI/pMxdNRz1pefnbSfvSNHYZx0GmOeeYaJvew/0tjElENVhDd30FKpbfs5aZ8kij2edqJJW5wDNi1n5carL2LnxglEHtyPOV7PtGt64+TpfCCqKu7WBlpxEGsJ69HCpRx3vpPAIgo0ROiZ86cxJ21TefcaCr2TiJmcRtpczQOjyArVq5YRbQ7RUbwMjhZx2XU3YE/OZsPf7yfSUwA6PQcTux/cabjZdsakE/pv8wQYsnAHcroNT0wEnonnIIgieaFidpsP0WQNIqIQNGmehFwZkqUthNn6YdCHIQoCIgKCAO80GzgSyqa5ZRixsd3f95iDLcwZ/DJ3pFm5Yt/XDFKKKJzUD3u4A5tVjycxker2FvQF+YQLAaoS04n1uxhJHWO9eXTYktETAiUIIS92WeDx4pdZHNLYnz2igG7QAVRRYCgFFLb0Z7eUxVBJxuruzDcSoEuZRYCQO8TljQ9hCdvBlNhVoCqYV1TgrDLjDIugzS5ibvMSSpOIsHnJmFuJe7MdsUrCnW7G5R2M3mRj16AIBtf3o7q+nYAtnianNuctaBVjCa0e4oW9tCaNRpFULArstB7m05glSBGlhNAWnuE6lSxCtDUcBMc4Ws0eFL1AQ4dAEJl2Qwf7I9eBGkJQZfQdqzA4f6IVKLIk0erxsQsdE6we5qYFoeEoSRVhiCcYH2qP37WNP1/+TxHm+1f3/YJA/L/cz3HwKwpVcgrpbje2sLBe2/xa0Wd89OG/FqZL3+fMV0Zpv9y4ERJyT9n+ttW7GG88+i/1rc/Ohv17KLz5FozhERiio0i8/RaM+3NxK5O55MFxlN35A7ScOudDFQQ4RW6JHFC5YXk7jTFxhMfORNKbePXz/E7KEY0TRGpwM9Oj550/f0a4cz+6oIec5gCRhSLlnxkAlQPBSpwEGZg5gSV/298Z1tEScI99TvJvIbKgloyQRhBW9taVnU90jaU0M6TnQVcC/ywHXY9SWxXlwGq8BpUJhpFInaXCJ4OCjoZgFnu/d3KmaR2rQg7+vlLLS7hWWsED+s8BEFSVmu8eYizvYbK4aRcyaPG7oVNxZnrZGvZtMzJ8fE9DJ9xiYPfZIxm+/wjRZ13JqHkDAfAV72DR5muxBCxMM53BroCTw8Cj4xIYFvH3XsdasWozWxQLF124kJ9WjMFgaAOgwRpOrVHjNnp39CXIEwxdZFG3pcVxV0Y805YvRRwygk9GDeGFAw28EO8nMW04FEHT7z7Bnjai6zx5nz9AfOHLnOYwcX1OIrPtQaKO85785ZxbOe/NIhoNIlvvnXbCOBevKKXi23IAJo7IpP+lWq5Oe8TjOJ/7hDBnK6OWfU3FH2/H/+IBhBuuIvKtt4AmyqPs1LXZUCkgWpdNpTGS9CPadR4zPI7B4g8S2+Fhm72UR6RsAH4XbOL0057hps42mY4XECoPUWx/l6x5l9D84Bs4D9/AwpvOQdWJfNqhmdkZWStoYitbZnzJloMf801tFXtC2nmPRk8kxprE0Y4KVrg3MMxSjSFe5qAlk7kLvkD8jXgJ6uvr+fr117m6paXP+OhDH34ziM6Cm3fCq2PA1/aLzc2KH+8pDIHjIWRrHBWTLruY6Egt3+HgXSYyc+wMfULjBinXGyB0ag0YVRQ1ldyTQGoPEdcuQ7uM2ywSEtyoghsELeFVFSBWhShVwh+Mx1i3DbOrEJciYnaLBJpFEMDZqUXXWH+0izBNRdEMh87f5/RbQTBoQJJUAqpERN2xfArNOX2eEsSKi2erpuLXdZK1ASDjd2gEaGavBzOnllMQAEe4TH1ziO8+V2iM3AdoC7kuGMmxIqOmr+8go30rbtFMxbhHSDvjVqYAdcDOS8di2+MEPmdlajpeY5CysAb23vh7VMAXUjC7Ahiiz+s678SssdjWRTDdPpsnLrqfV45s43A1nKo4RxJABtasWUNZ6bW0th5lhHkP+zriGCseosKSSn2YmWh3iO3zR5C58SDb2ly0et2U6hN5VSxB7iS0M0oiuOq0GfNqIbnKxqMc3fI2swpfRkHgcIeZvyW30hZKo8p/HqUl+UyfcCGZ8RmE5EKNW6QX5O9t4BitXmjpB8hTh9H65gs0fql9h7YsG5jtuAQVPeD58GvqU2cTX78L85AOaI9BQEBnimDbiDMJb2kgUQkiVZdjdbaxftwcklSFOGcb9UBTSITO2/Zi+z9pO24sJe23Q6ecTsdTL2D2CDRFOgjJCigqAy1VuDxGmtgKwPSlF3Yd218RyTcm4DQOxak6CDhG4CBIgn8lGFpp9bZw6yNPc9O15zI45dfPfBoZqVUotbS0kJaW9gutf13oMz768N+NyAww2qFyO2Scmi3ArAbwnKIE9HhIZu1R7/d6Ac34UCQD+LolygWjEeRfMD4kEfUUBk9EhMbaOmxBJJPmDT9hf9W6SlwlmqBa2f4mYmbNZPRfXj6hXdKVFyLLMpe9++YJ+7TBK/BIBH5HJrY7tmECfq5RXfTWs/SveZQ7n52KoOv5aPns1RqqWhswiTbMulO/lYqCQHRWAhMfms7hL35gx+Zw7pKPeUumk59eRXbDt2S0b6XRkEb0vftJ+1n8Pcqt4I8wUDhwLOh1ZG1eR38F3q34BkUUQVWwKU4OHDbx3YodbHb76Wgt4pZyHYnyGu7ak0jx1DQwm05ZMh3y+wmJZjZt2oQgCCQk9GOfNBpPex5fXPE7LCYjGYt3EaHXsWf9Gr76toh4cwZf1T3JvbZLqSaS8Ewth6NJ1ZHRlAdA/y8WsG3Q7xlZ+ClRgo5P489kRdRE1v/uT13nbve5KBraiDfo5/Ud3yPbdiMZhvUY3/68BpZ9WURYXbe2luuIxJGZ5/Vo5yp2cWTUGOa8/jkZFYVcsOxjEGopz76TAWf/ldSmcM4//yNESeSPa/cBcGd0NTLjKW5S2IGWyzKtcA+D6o5yt/Qx8yNrUT/Px+JykjDwKgxZw/B2lOL31NJ0aAW6EjdNMjSlCmw+P5F58mYiLGbOC9/B2IrdHD1o4EBlNHEmA6oAMfOvYK0vnhqjnVZDKrdLAu+2d3DWWoW0FW7AwPuz5pIYFeDj9z9i2MQcLp516Snvtf+/Q6/XY7fbaW5u/t8eyv84+oyPPvx3Q9KTr7+SbV/2Z+ihjzujCJ0x4uMXNAHE5FTeEtJpXlVISyiEL9qIYBSRBEHTXREERKFTf6XFxR+B/S+8RUFkNKpeT5K/g8PVzWz44hCiAB1CHDHxoxFeXQyilhiKIGo/RS3U0RGWgegrZfPmVxBdLgy7y5GiRiB2Vrt4fQLQDznQuxHj+akci6JRXw+1SHjlE8Uf/yV0zoXXloHtJE06mvx45CnUflOMyrEkVxVUGBM5mjERYD7QCN4QRW+v6Sxe0SZMEIWuzyZEftxXCWIQ6Ic6JoSnuQO/y0tzs45QTSxNQg6TpUPEBCrgyytBlECQtARNUUJocWEyW8geOR3F56e5tYaoQ0c4IzQWY1ouAX8zSxo/It1bwzfeRNoCJUx35VMTbaE4PIb09gyU7Tq2TgP1FAZiu8eLZNHEMe+9914AHnrtU3SCwtG6ZgalJ+K16ihWtTBRethQfGHl5E6s5hXHPtaKs8j58RPIOQcPEokz/kJp6Ub6Ne5mfMGHHIwZR7/ff8GinXVsCHSX9PqCQaZ9Pp+Q2F2too8DRXYCF7BzVy2rvy0irCWEJPWsKYqcNoKEQVMJNjXjLWlASkhDlRVNsRmweZydX7me1Cmv4OzI4fwLPjwhlPHPpugTchV8Oq0axWW1klq7FZx+QKRyQzXSQTeqomJasgSHLAMSt//ZQJtNYV57EXNajtKiM+CRJOr0ZvSFRjKLQGcLEHJBW/1CHhn2ENk4KZ8LL8gq2MLw6UWWDrOhd8YTEvw0xNWQG/Kxf6vChTMu/tWHYKKiovqMjz704beIbTXT8IQkth+wYxKdHMtz7y7v1JAuiBxMlfhccKMIEGoLIPciDw8QL9o53xxO7PIf0CshDIrmg96g6vlxX4XWKKIfYY5M/nDw5z6E45B5PXGGFUT4XwA9uMdA/F3rqLcIGILg8Fph0j/QV1YCvSdxuqwGBv99PJV/XYPd2HsI5xdlqzqND781Bf+BTchH8xBt4UgpA9AlZSGYbCSaB9LSMQXj3sZf6g210Nep8CsiICB2/hQQCSFTGapg0UFtrF3LmwBYgqwITQGmUCD+HpMQhPwfT+jf15gIeOG1RwFNUE4BDjetokJarfWr6GhRorky0sm3dbkEwg3auczp4INIp8z4Ai9P6UpJKN+DooLSWdGkdPZ3RIhAPNCG3+/noUceoyAmkcKEFKxRDr7eVYoprx7MWgjsLksy89seY9wcTTH2HNpYyywO5ZwDwMdN5WwOdmCceA/WqnzGVqzmwKhrMVXls83pQzHZuXNXCUWBIPHeBtzWNCCdTHsuFr2d/Y37qa4X+OK9RTTvsBIGKDY/EaZa/E3pXXNTWOmgNToLWUpFN76IyMgORHSIGPj+iz8ilrgIq9IMrrbBIWqH3MWqVasRRZGAKnL65gOYE11MGDuC8LVVDE6I58XYzXxbew7Woy1siR3AH9rbabWGI40QCfe3Y29YjlQj48NIm2TB12884YMu4FlRxCJasDjfBo5iTrgciykGBIHKrzUNmqjzZlD/0RpMZS4+Dz3A1qkzmPZ9HC+co3kUfxjXgDHXh5lKnkzJ67rOCPHTX73hAZrxUVlZ+b89jP9x9Bkfffivx/w7xrPwsZ3Yo01c/MBU9MbevQPXHff52VvWYj4tlpsvGtKjjaqqyCp8V5rAVXn38/xVozh7QByyovx/7Z13nBXV9cC/M6+/3X3bKyxbWPrSQQUkCCpVRU3sXYyaZvwZjS2KMTGa2I0lFhB7iS2KiqII0gSEpbcFtsH2+t6+/mbu74/ZwkrbJLgL5H4/n/d5szN3Zs49b/bd88695xxEROMRs5m/CR2hw+w565hfUsvPHz0VoUWMxFq6jtB0o55KROOdp75Ezcxj/KlrKFn9DuPDY+BxSCm7h97VifzJNQ3WgSs2roMcdc1B3rlvGeeYreALtwp3uEX9h0WIlqBDITC9PRObNbLfMQj4YrFYfotGatt+vxLC10slbWJfErKTMdssvP9/dxEOB7n46Udb1paAEDpCN0KV0QWPX3UhgyZdwFM3zDioLFf/+WEWNw/Eh51Gq5m0CXdByNshLWpyyQvUliURGnUZA+/7FY/O20hUQQP3TM1nUL8k3I0Bxj7+LT6vlSqPm7G6ICL6oKoCJawSVtzEB+ycuUHwVg8nRS4FFYGKaHHQGNueNT6chI05KD1C/6pS+leVUpKQSkGmA69w0KuuhpSmBmIyS5iQt5rAUgfvjT+Hb5lITtlurP4SCnMHs17NoaDJDIoFolN4cdAE8GO8YqIwB3fzhqdlTYfqguSbASho7XTqSKyRrdyxWeW2ll1qs41gczZ7XTvp6e4LQFnsSPYVhtBNsUAK/S/8ebtyLwK1EWLuMjwY9g0qWyimOVLN8nAOe/U4oA95JaXkff0cNUCxYmW6ayTzExpYTm8SfM2khetJox76Hfj5PTv0cnKVU0gPR9GjBEDgMpvBDI6yuejCMMYjAcO4qHrta1rNY3uMl6FjP6SmsJjL37+BBaNvQ8Hw2Phpn56s8w7n9LNPOejzc7yRkJDAhg0b0HX9hDCmWpHGh+R/nsSMaAZP7Mmmb/by4s1LOPPkVJIT7cTOyDWmAw7BwY4oioJZAfN+R02qgkk1gbnVqFHb9gNYo6zQUq78h5isgLBiMcVRtnMN5uxRRBQLqvNOztgVYAmGj2ZdeTN8v9sYyIWgwuNnoOqlUvEhEDQ//AJR9D58OGAnDJOEba9htkao9I4k0PdkTHWVmBv3Ee3bBnFPsdh2Nufe9hDb560kba8dRwmE5+2hCiPvRKQ5RFgNtUTQtOqjo7EnFOWw2WOH56ayeCNoKKSF/LDwngPaJGWBJS+N2LtvQQhB1eZGEkwqw/unYLWasSWaAYX+49K54uLJB73PjnUr+eoFP/8ckkt6dt+Dtrlm5dN805hDI9lURHwMNFUiFJWs+iqy6qvo3Xclu3eOASDXuobACAH4+d0/B/Kbb26i+upZOK87j1mfnstvxjzF9X0nous6AT2MLxLCFwkR0CPctuY1Cms+Yezgl5nfYCxGNSuwID+VHfuqWbViFc6qctyamZ8tXoBmcmATEa7/eSO6oiPQiQ7Fc/m6+xgxzkaKo44FXxkZTyf+ZDMNW54lpDWzq/YbAjHl5K79Hl3XafT6mfPEmrb+uhQ/buEg0dfu3QqLEBub1xA4fypqdYCqjBRYBppiQVd7gWIGIbBoOwG4ctxonvr6bfLNd7Rdwx25Gnfk6g663X7BO2xQk7AQJoyZ8ae+3vqvw2ZzNO9Fhwj2fIakvTe2nCG4v9zOhOIZpOT2OujndTySmJhIOBzG4/EQGxt75BOOE6TxIfmfR1EVxl/Qh/TcWLatKMexvZ4qgjyx9jVMqMy6/joyMjI6nCOADR7fIa/ZWi/kcIlTFeXI472iCuMHvaqgFE3iFt8LfJI4g7HrBGB8EQWcFdQGdrFnfkHHk53tm2qzwlWmfij2Q/3LH3HihZBmwmnxU7cjioaCcuAj4zbjf09TYh4bmpazKynA4sXzSByZQNS5p1H37HbsensEhqqreDmwXP3+CNTDGh9D0lNhY6RDwb/w4BsQrkxaRyd9+V/xqhnEAh8/9Dfy9UwCFi8Ws5E0zdQyiIW1Q38C3kYjDHrL2reoq8nHFd+L+ORsomIS236BnuxeynprHEsbLEAcj9sfYOWGgQws3st3Q/J5cvAtnMVKSqJLCC0T1IbyyL9oD7bYTMKALzmZeNXcol/Dm6SqKk7VhtPcHhUUZ7GhCh8vDMnmvt3lvLC3Fk3XefWjL3DuLW77qFO9jTBkEKoQBHSdqzZ42ZCuE1adDN7lAAXWLQ8CiahKGFfuMr75dj/Ph9nQoNXp5Lz732Jm0ZeQdgEAiTaBzRGPuynAtqg+5Fh305qhYtG46SgBDT3DCSrUmWNJjDRh0nbjsU4DXQE9gMCKt0kwdF8MZMEK13pi0hMRmiB9aC61vn3cuedBzhFj0EuNNPfjejpZvDdIfWMGarWHLM8N5G6uIHheEkK1oSsOVOHnj9U+NvunoetO8oYcvNr08UhiS0HC+vp6aXxIJCcaiqrQZ3QqOcOS2PJpEeHvjWJOGjovvPAC48ePZ9KkSe21NYAk66ELy7Vddz/rQ9M0KisrqaquIj8/v5NyQTDk5c3PpiKiG7Euz+K8qJWYzEY12+29TCSGdpHYoz+TRo80kl+pRpolXVEI6Dq1S75ieX0FkQFVkJ9Lzfp1tObmMGSEUCRMQCgUF5dhMatYTSYsJoX6YD0CoxbJwt2jCOc56HP1FJw/d5JgS0CgY/rE+HLMjhnOLn0j69fvJRKpZbFtA3nObMY057PeVMxWcxm6uRr7EewcoSgI/dBhRaHCUiCDJsbhivbiaF6CZdOBUTphtxFZ1FwWh19PY5jpI7zNTUS74lFVFVWAph36Pp5aG+AjqHxNledVqjxAKehhO3ogB7Pagz6nFfCotpaeD41Eq9pI7YXXU5k9nrL+NTTGbeOPBdtZH1/L90nfc/WaLAQqzQv7oVgMo8dc34jdZHi9QodZ2BpjsoKI8H7BJtZt3EpGbBLnbDQK2nnik7ngogv5au6LOLJ7MfammwB4+umnaaqtJbvF1jM3bSQ92fDM9RpSQ+8pqazd/gYaCvE+GwNPeZuSL87D7vfSmLWb2z5/moTGBu7K8PPYiIuow0a0px6sTtwRF29nXIhLV2hWBXox2IpriPSKIjIgjtGnvM2fK4sZt8pDvbU/hUGdLKuKRxek/f1eMnMmApDUnEpkl0aels6Gig1UjWoiqIZI0xNoCnqJWGyUmnOAIorWnY66Zy09kzzoohQRbxhnZvtsfDYHv02pJLf0eSZWTGRfY9MhdXm8ERcXh6Io1NXVkZOT093iHDWk8SGR7IfZYmLouXlwbh4xBf15/70PCFmaWLZ0OQNzR2BSTUTFGUW+e9gObXyIg/g0Xn/9dYqKing/533YCDGRPBRx3UHObkdRBJFQE3HmcswT/4/+M1OIc/Vg+a4Qsz+txeTWuMIOMekZDBrW56DXWLD8cwA+/Px1lM8OHyv8/u2/aNtWzT3pMU5Bj9jYt6IKhJUl9kperDSq2j53+nOc2vNUvtjxNiklUaRMUPnpl6eQdEtPysp3snzVIraV7WOLvb1arBXwKc3srS5q11Vb+nSjGnDIpOP3+qmqakAxm4loYXxuNzan8fu+qtGYptHG/AbTkD74i9ehV5W0F3BTBN99XkaDKYuYajdNaiJCaGzwTKV2WTH5wxXMVgsqED5MEo+UzCxgG3k93iQlR9BQV4KnqQyvpwSvso2IKMIkwFyhYooyoQEbK4eCCtZAAvF6HL6YLMKqkSCtJrmZ5Jpo+mk7EFtuBiB6eyEOk/EcBfVDGx/+TRtRHBE2f/IBo1Bgv+TnPfv245S0ZBarKlqLx6impob6eqNez7XXXsu275azbtdGTopqSWu/O0BM5gQmZOwkULsOW/wAVGsM5o0/wfev7/A9cjYJQHNiIoOuvpgP/nIXuqLS/5xy8nidtIjCFc3G2oyN1ghfOMOA4Ja0p0gN1pH1/c308MRiispkqydCoyaoiRiyuQJW1GAhgtP51mosEF1h2cFgJYVnql8HoHjFd0Q5+yCcKo1uw5DwWYH+I/m8eA/RWgO3vnAvGpBmz+LZ6cNxe9/lzL0Z+KwmZo7oGHJ8PGM2m4mLizvhIl6k8SGRHIJ+w7P4Rfr1bF9ZwbYVFXzwV2NaQ1HALqA8GKbA7WNgtB3bDxeC/aCk7fbt2ykqKuqwzxO9CxV45sZFxin7GSytWyoZxGTu5aNd01hcltxyZG9L+uz2e6rejsXNOpCSAtW1nDnjpzhsto53apkeevfLr/GGBSddeAWRiA7+OhpWV5DY38gJEul5O7tDWxnTawz5mpdP9nxCiaeEUzkVTWioKKjeWjRcrFg9HWEOkZkFmVkghBE9VFOdw9f2MKvS63nr83MOLe+ZkFqYwjOPrzhEA2NRa8PXbqoXb8eYXxrQocWq1BpCyj42P/sYJLXvz3zme0K7d+NXVN42Wfm29hq+sTgwmRQUk4JJVVFNCqpJob7CqAuzfcUmvnihCtXcg6hEJyedP5DY+IEoikr9i1+Qsnkvppx0KNqIMLtAh5IkG69MPA00nfF1Pbn1s0am9FhIQkIDVlWnLBwPONjRLw9rGJyanVB9Hfuqy7BYLFgsVqxWG1aTFbNqJjejJ6sbIOnUn7BnVxERm50xAwdw4cih6LqOPxBAFwoiqNNYUcecf7yAFROKMPPVk0/j905FxPySQm07fUz9KY4uRdu0nJBiwm61oTaXoJgteHwCGxCOT0GZOpXsiy/C7LQSPOljXMkJiPm3wDb4qbd9SqjaZBi0251XYt9oGBiaejU1zhsIaOPpr37IzuaBNMX1weptxBr2UGjrv9/SZBgydAHJy37Ovafcge7xk3FOCt8t/pqIqvKzqVN54c39ShBkp9GMkRXvpHAeQ7QsJq2FzY3NrEo7hVEOnSTn4bPoHm8kJia2GZMnCooQR0hI38W43W5iY2NpamrC5XJ1tzgSCQCRsEZtWTOKqlBT6uHTxSX8q5+FPSkWLIrCgCg7Q11OhsQ4GBDlYFd1M3fM+Z77Lx/Glfk9uO+++9quNfbUsdj72Ln189fwO77j/MBD5Dh7dVgA0poiY+22NXhjazgzt0fLTr0lakVQ4VfRI2G8FWXMGJ7O6Jk3ANDobeTPz/4Zc8CMSZgwayYUFH7z61+QmJx20P7d95vfgRDc9/RjNAWbOPXtU+lRF8PP08N8mzCe3+RfQkJsJvHOFDbuXcbl3/wKVRhGzOU1Z3NpXXs9GPPML1EsKihG6CxK67bCE9+/zgrVwvW5v2zpp2ivCoyCjs6Dpc8woTyfyT2vQGgRVixZiFfonHz+RQDUFBWxd+0yfjV8OvEpsYbnRIDQBJ4ysHhtvGQ3wmknnDQFIQTbFrxNTWIC0W4Pk/oNQw8GsT/3BIW5MynPPPz6gJDnA/RIMYopBWvMZfSefjfWGGPBZeqSmcQFzwPAv3Yu9YOvJtt+Mf/XcAvLMoeCJsh3VTOmbB1KlIPsUJCeTRtIW7IXoSmkjWrE1jtMWfhNovQDB8xtpjJWWHa2PRpzxpyBbnYYeVSUltyy+03tnVcW4u6t7QnF/tXY7k3xKoJnYwNYYhVy3KXsFJkH7e9fcTCuJY1sqx5b6aUlMSeQSb1iZoZPZZ0NSi0h5loe5mRnIXX5vyLi7MFe/5/xOw8emfHPnVcTtA7kj7ti2U09e3L/yUCHSs3i/hS617a1S1di2Nn/IOEy+/HFgFEUpfQk3uvmp+sWYz7MdN3R5IdVsPf/+2Dbh3rvTBtFUQgEAlitVn7/+98f1X4cbf6d8Vt6PiSSTmC2mEjLNRZ7pWa7yP9JD36r6WzzBtjg8bHB42Ntk5c3K+rQBJhKm7EA976+nn0T3MQPPZ3m0q3ceuPVbYXfVOdfQMAHlvs5O+16fjvmfFKj4zvc96O7FtDD6+fSiy4/qFxhfzMP/PURrPt9z7+9/G2ivdGE0kOkp6RTvnETsaXNzPu1McUzavQ5OONiAQVFVeg3dQJCtFfN1FqmIvYlergvBFQuZFHlQgCG6CauSTmVv1bXUhXfk+he47AmCYKeXaRZXKjxsTjG/OmQenRsX0xysIZLJt5wyDZ/f/5Z+iZHc84VLQbNivepbWzginOMDLTFK5y8v+KfRI0bQMJJ/RFCsOXNldi2+XHoVtzWANHOaCJ6hInTjUiTEb1cPPH+e8Q2e8iZdArxffqw+R9P0bNvIpNnj2uphaOjaQJdE2gRjY1fr2H7dwp9x4yldHMYX8M+BPUMHfYyDkcUutDxriiElrHeeco4UqbZOOPj31F24Rlt/Yldtwct2nh2MuK82AZPIfYnJhRVpz41BiUYImqRg0BSA80nJ6JFNPSwRqDKx/LdO1FR8cSaiG4Kc57VRLzVWDCrYkRMGTnpFJ7w6AT8tXjm34255wjEeTOxr48m0GK5RAmF2xodRKtzuMo2n/vCVzJPm8oVgx28u72RYNh4LguoYxwHGqk1ph4U6w4u9kQTAawoXPP1b3BleEkd5sZq0shY+yg4EigcbTxLffRbUe06QtPw1GyiImERF/SdB8C2TAve6n+QZ7md6j0FiLOy6K20FwK0P/kY46u/Jf66nyO0MHWvvsaXw01szVLR0bl37l4uevsdAOafNpmqXumMyOuD3dyxrtDhtn+474e/xfdvJ4RA1/W27cPtO9Lrh/f74b33398aYuv3+0+ocFtpfEgk/yF2k8pwl5PhrvawEr+ms9sX4KuEWp7YtomJ/ZL5eH05FU0BoCeLn/mOP5w1kAl9k8lznsYG7xuoIoZPyp9g/rsvklo8CFNoBIHcrZjtgqp+S2luHnZoIVq+rz5cW8E3BY8ghKBJeKlyVLGFdWg1EXw9w+QRzRWBaRTuWcX3azom5WquqwOhoyjG10GCI47nB77MZR/t5qlTGolJbmaft5JYAQuLPuOMNa8BUHzuH8nuc7AKuIcmIkSHMOSDdkkR+4XhtvRxv1P0sOHaN1nMFLyxFIq9JHuiqEnWMZ+SRP8x/fjiyc2EA+2/+uMG5zN++TKWCcGTb7xBXmkpI/UwWlAjKu7AWjP/uHERWstNA81RTLjmND5/7A1+dkcu6VntUzz+AZthjR2hhbCkJeP+0EdKkqA1JVQvrYjzh72Edd3ZRFUuZ+I9C1BMHUOLNY+PikVriXfYyBs/rm3/7lXbYPcaJvQ9ieVp0YS+/Yo/jBpMSkzHHLOhUC1XvfgSw0PR/P75pwGFHn0+om73pfS3m9ge0NoMEICt3hlgnU9iv3E8lZXF8x++jrCe1BbGWpe6GKouBiBJj6VWbSIgzHzqTcelhLhuwzPs6/ETcoo/QxU6zfsc+GutOLMFPS4+CaVkGaCSEkym17T2NUS6rhO38mXCvjo2NRTiSFrE0rptRNt6kJjZi/zUDEbl9yYu2vAAPfviq0ws/B7uvx8wJtf2TIeyaDMxis6lZ/6Ne05+mOzYMsJLLaSlpXPphT894LM8ESgsLOSNN96gqamJ+Pj4I59wHCCND4nkKOIwqeTHOMkf2oubh7bnGqhtDrKupIG5y4u4/tXvWXb7JIRQUHQHyy+fz7LiHTy05EEqe68GVgNgjiSCCXpH7z3ovYQQEPFxSrgP/mgvalwsOjpfh5aiigCjAv1REy1Y6lTyrLlMueUmzolxdrjGs5ddjNB1dE03Eke0UL5tBULrzZQJk7C6ktv2z4j8Bf5sLKLIdnYMP+4Ma7RGSpUj1LMB1P3WswS1II1C49GLzgKgTz9jgC5/fSPJlmR8qoWGfIVhl53R5qpWVfWAX7Gn33gjo6uqeOy559jVqxcjVqxkX+kG9IiGav6BQbDfdkOlgqIa0xCl21eQnjOy/aBTRygRIopg+5b1ZBdu45Z714D4h3G8pRv2xr0kfLqXyoazSZ/7WYd7qVbja9ie3jEEORg0XCq9h/enpLGGPcDqKg8NpW4aQhE84Qi14QgL3FXM+nYZ3rwhtFppIqzSZK7F7d3FsJhT+c7b3qMiEsgOvAlb4Y7vb+KMOjtj9F3YL72S9Nh6/lq0BN8Fv6N3WjbTCrP53Wvf8BeRxq9xsHNALCtrUoi4d/Dbh/8GwLOfvMbAHd/h2VFPwy4nCfeUYPkilxhH7479VFUyxs0CYOtHjwCLWF+nU+7XCKoR2FQCH5UQTZBB3p3EJqay2fVTfj4ygex1DxNRoTDBePamKakUBE3M2lDAXhJZ6wzjK9nNicr+4bbS+JBIJJ0mKdrG5EFpjMyK54zHlvDEVzuNtZ6KINpmZ2q/oZyW/TLTXpxAbYwxCN3T91o+2/ZXXKFSeGj/ipbGoBohwt56K/9UH8QZTuHvvzgXgPO4hNLbl+DrH6L/5Wey5+63iCx+i5LPl3WYaxaAnqyz9fvPiEfg9Ot8McHwZNiDGs9ak/hodl3LOfudF3rY2HjoezBv6nAsOgam3XfZIZOzleqBg+7fH4EgtNWIgti7ZTWjXZfSx+VhbfoLFKSfRNGGKnIAFYXtpn0kjc9i2NQxHa7RanwUVRWxds9abMKGalFZtnAptpaSeJ+PsJAbKw4wPAAmnJnJkoWG/6LvqFjM5mYAynduhGnt7RSTCsKMgkA1R7MkTRD1Tl/8/QXVeiJLMwqYVuFj0gfLiTspA+/mkgM7rLbcXzdc700V9TTXuvl00QKicZCUmUrTvn0A/HJPGSFLx4R0loiVXVmZpFmsvDD1fGIClcQ2VEHDazjNLvLjx5NkVqgL+wkpVmrNgmxXCXed8jh7yGPDnpNY0Ptczlu7GE0r4bFRAbxNuzD1zKX3gEwuTOiHq9bIedJ3axN9ky7juv5GTZlflr3FaVHvENU/xKgLU4HvSHg5n9/3VNitf0fx5yNa1qS0RzQB2J0RdOC1i4bQc+B43J5m1m7axfodpeyu8JBTtKyt7fIdv+GjPr9kcOwKUrV9ZFVHcO29idMjVtbH9GaxPgJ/YxLCHDrkM3W8Exsbi6qq1NfX07t37yOfcBwgjQ+JpAtJjLZxxSlZ9FtUzi8Yy9IYO4sefxswBt2H6mezoxCqtSAlmxVSLFdhsVXwrqhCRcfs8OHKKSKJBlRdQe0VJj/4Li8XtZcdD/uDHTwHAUcxSl0h9uGTUNSOA21/vQm3Xac+ECZisRDINBaJxe8tI7lyHZUJE+GHhkTAi+6rwpsyAJeu0Tqo1DeoFFVnMvcvt6GY9LZkqq1DjhAwKNXFFoubc94d3RJpI0BRO0zEBKwQDFWxdNIoksq92EZei2W4Qs6IveSwl9/GvUn+16V8HdQRYQuWhVWcu/hTAPKigpgUCPji6KEqvPLcKx1Et2EnrIQImkLY+p3ODpqpL29GNSuYzCZUVcFkVugzPQdXfwuf/H0PNld7SHW/kyd11EWLbsyqhbRB/Rk365f87aGH0JsUIgIs7uGkrVpCU3aEpPgowu7yAx8Kk8I60x7KNtfi3vwXgrR7hq6YdiH2aAdxmkId8OuYWAb3TOKGed+jaAIiOqpSyx/uuZt7n9iAo/EzYv3toc01JgVfUylDFj8AwCdD+zDBejbZwz/lSuWfRqOWsWx7ehY5NVtZUHgW1TuepmrD//HimR8xITUGUVuH7Wd92bBwN/2bNO6qiWJJ9XpmlK4kweTBl3gypzdX83W0Rr2q8GaDlWmhvuT7+qDazFgyolFMKt5aP8IdwhJrQq22YolPAcAVE83EscOYOHYYuq7x+CX/bP/MRCMRXyqv51zI7aaHebu34LWkB5lWMpMPlXNwNY5nz/AAHr3OKANwuMx+xykmk+mEC7eVxodE0sVMH5JO46JKADK0HtCyhiGtKZ4ozUmVHsETcYAHXK4YQhY/gSgzugA1voyYJB9aIJmwohMKBRiStpFz/SPxVpewc+2DWLfkE8tQTC3ZTIXZqMuSOfcRzA4HBW4fr21+lQ1LIuxuyuGzm8YzMKPjyvQtD7wArz3OaX+YdcCX+SaPjzO/N1Jlz8vPYWqysZjy9SffAzeoFjtx9hC0xLGoobBRqs+kMNRmI9omiIpOxudrDz12OrJo9aCkqUXYe+pUhhLZ1ctCnTaXsdm90FGYyw2cu3snWrAHNlsYa7wwsmeGjOygdosZTUCJnkCTsJNuLyLiNI6ZTWacDicOmxMnUfiLQpgDubx1/+pDflYCnS9XLSf3rQKmbtwNs+5nq/JHUIxkaEpYwRSdhnPSbEo2FrDgmjlEoSAIkzxNw79rLFlJw0lNOpkAAseYUvhjAn9MjOO9mCgGaCo2FHpbzu1wX4siMCuCNcvmsm65wm53FABLF6xllSLoF9BwB0OghhGKzlUPLmG3HseNgYq2a5yWups3o85insfKlS37TOjQex632585oK+9A+tpjDi4s+Rt/mb/GQVRRZw1/6eYhQVbHzNZBT2wpVjBpTPYN4h7LpoN9/2WvYH5EIC7Q0XsNb3MDkctG/1mhlUP4rS6aViUPSTsfgiLWo4uHJQH2w0L0/tXU/9hBa2ZUjerfah3xzAKM9ETVao2XUa+PULxly/zs/k+vhmay0ANVk8voTG4i37uS6mPMfFFbg+gBw0+PwlRzgP6diJwooXbSuNDIuli+qe5eHliOknfVBIXk8WQm0ehKAr77vonkUAAn7cJrD0BEIpOtD2JK38/G4DvvnsEr28NQ6aswWQyEwn7WLJ0MLOG9+K7zZPABoxYiGX1najresIltOXyaDUi3q+qRwR2sLvJiMh4eX0ZD2d0LJAX9ASxoR70V+QuX3so5zuV9W3GR3RcAk3Az268k5hYY7BsePddKu+d3dbe/PhwhhFi2rTP+HpRu/v4tAkfYjIZCw0//ao3RaMHc8HvPwLgyRU34Q98itdzCjcnxmMdnsWKHRFm3pxDRo5Rc+Wp2z8j22bjX3cYYbPX/P1TNlWZefQPjx7yc7j/Dw8RbYphxJQsdCEQmkDoAk0zCv95PV5KNjSh6lYqMtKJUiLEx1rJHJQEQiB0jaZ3t+Oo20eRuR769CJPzUAIgcu9iWu3nWn0zbSbdLsLJVyCmjoYkT6a92yGB2SbSUcRCr0BNexH9flIiQnjckUhBEQigqAAhEaxnkRtSBBlAtVkIjHagYoDkwpmRWFQXRF10QP5U/pzqAi2OqcQq4ymzFLNx6fOJslXxQenvYPb5iG+/FaaE67FEtyOUGwoIswFOW+xLHQ689aMJIViyBIIFcKECBNiC4UA2J02Ki1ubgXCjgxomUkLBnK4oO58Hs54maAaRmyZT0Ppegb/ZHmbzlXFmFKcT4haBIHSfoy1RSj0JDEgtpoV6WM5ZfNKUkpLaRJTGZKbwqm4YcofMOsBJtcsJoog07ZkkVpSgjP57zx92q0AZDTU4K9RIOrESTC2PwkJCezatau7xThqSONDIukGrpnSlxKrncQvSghsrccxKBFMFpRwE5kD4qnbDRdck8obC3e2pXHQdY2GxjewWo1KsADNu9cb76uqYEj79TVrM6H4FiNho9Gm8A+XothMXCrgHXc2N4ffR3frDPkixPbFfjxVUagixcgyWrgTm6Ly9p/avQImi8r0GwdzXmo856bEsajew8Boe9txl8vFPtwd+ikikY5/C9EW0jt61Ec0uddjsya3GR5g5K5Ij2oP9UzWy/FoKtNnzMVqtrF97Uogwv4Rh6qikJ0c1eHvI2V8MJlUEpKdjDnv4HPo5SU1lGzYRLLFQqXZyYa8AZh0jT/8+s9tbVZXPAAfvc6magc5PZzMuP50fvP8yYRsAvYZxkegsQnSQYtNRPWB23wdq6eM4sFF1/FhuBqhCN7PeZ+rPzPW9Xit/el99mWcfuHwtvvsfO8JPvnnQv7xzHPYkw6en+OVX91Dna+KOTWGZyHaIphue5ORUe+xu08m89Kuwi2aiQ7GQzBEin8uzYobVTdzR1MxGVqYcy12UnPuYIf7YT7cW8EnQ89lbn1Hz1BADdKveDjP3LgIoTyNIoxpIocFws2DuK7+jyRsvpveNSEafr0TSjvK2dN+FpcJO6v0ASymJ9vcRrqxTY3p2NICbBk0iBh/iB5JJ7OtogDSjc8nbHHwwZWziPY0c8lXnzGwGp44eyYfLtFY3fsRiiry8LqGQfaJa3w0NDScMOG20viQSLqJXhMyqStrpv7dHaTfPhrVqqGpToJNPiAK1aSiCx2rYqw58PvrsVqNwV1VzWx94lIqhqwCQAnUk7XwRcJmP1+oBWxSG7l59kwAQn1s2AsgsnIHmBRQ4AJluyGEAlRBGAUak9Apx2QxYRFQnTyMxiqjeJ6uG16BHasqGTElC0VROD3x4EmE9o8ySbj0UmJnzACTCVN0NHs+vYjW6RWXazAu1+ADzweEaI/OiOhBNMWKtaXQmmoyztf2Kz6n/OC+JlXhMJnT287qTI7FwePHc/2Zg1ny5JN809DQYV2BM8aQIS61iaKNyVz9yK/Y1SOIV1fAWCNKkncr1yrJOHzZPAM0rhWE33uU0BgNesGcwTcxa9NTRBJtmBusWJxTGD6+Y6r8xnojxfjh5NVtxnqeS24dwcLnNlDrK+GL1AE8HHqAu70v8Ul9HjfueKLDOWE1yEsD5vLT5i0ANHjXUKX2ZmLyKtRIhP9b+x7XKQpjs9sNnrv0AOGoWDz1oOyXyTdNXUVjyEZNXYTqXvfTL3gn4WzBVns0A3c2d7hvjBLgDFMBc0+uYlO0mQFFMZy8JZYLln8PqkqFHuDd2jd4NvfGlk8KUtIjlALNMdG8eN6FpIbO4JxlsAidtJJ4sIKmn5hTLmBMu+i6fsKE20rjQyLpJhRVIf68PCoeXE3zmkr8VQp+TWNbbTK9LHtJGjUJ/fOvUBRj0FWU9oWPDQ1FNJavbfN2ON1vkf3ggwDMv28VVnN729CEXOpPW8mkiYUoSsdfTK2p3UEHVEad52f0lBltxye2vNfu9fDOn9cQCnT0ZHToT6uL5gfjo2m/SpwmczkWy0EWXXa8EmI/v4X+gwG39Vefvl9ROAXDQGpr05mKwYpywLU7Yhxbt/YdVm15msbGdADW3nw+MdEWTCmJCJ/hbbnk/gtY9dF3aHGVXIOfm8uc9E77E2OWn044vz+zq+bi3BTCa0pDbzQiXoZZo9nSA4YMvAg2PUXOtGxG9ryd3GHJB0x3VewzMqpqkUNX+22qMaY0EvLiOPcvJ/P0lQ9jr4eTgIX0JDFlL62VkPMus7KpwINjq42Lt/2c21xXcnpOGbuc8NeM0TzXZwv53o1kv3MeMULwUGUtb/kTyKyGlJk6ZL1IbOZrRG3uwyK3UchuevxDlPtieKt+GFqokNp7jeiTijQ7ZdWCKY3eA2Sua0mxsi3Hw9T1ClpjCCEEq/PSMCHIa97Frug8BFBVboJ+OphVBhaVAe2eLlNNFPQAT/Vhygwc5yQkJABQV1cnjQ+JRPLfoUZbKA1o9Pq8GGt0Muu9EQgLksYOY8vSfXi1Ory+OgoKCmhs3AyAxZJHKLyJ8GkjaM0Jsj59AL6W8FSvLgjWVrNlydcoioK7cQtqPFRW/ovWkEeBaBlbjS+02LQIqqpgpi+bv93XLmDL4OxvNlzrVUVutq0oRzUZNVBMJhXVbNRCadxnDDalpaU4G4zpGEVROqSJbjU8GpvWtixHbXm1pF8HcKo6tSE32+q2IUSQTG0bfsWK17sHVTUT0RoACwFvhHBIM+qyKBDSBYGwhs2sYlIVI/X4EWidvjoYPp+vRdZkwgEzSQk+TDU+lB1lhH0BtDoNc4stoKoqY84fy4uLRtJPbObGlU8aB3JeptB9DRm1Cv09b6HTHmq7qaeXYpOJ094aC6pCklZH7+EpB5Wl36Acdm0v5vmbf2PcDxPZOUOZ+Zf7DuqCN5sP/GofnROLb5fAPiCWKeNHMaSvl1cfWk100Ex8o5ndBf0xX5lNOOhGCMgeMIkNZ79Kwrx7eLfXLDaeks8jS2ZRVaxT28dCr6ZqUpx76WVdxuKqXN4tGUx9yJg+E1oFPl8sTmcT+8IZNCXsJckfodpsQgHejYlGDWWQV5tPoMdigprC+f+YR1ya4fH5tCWny7SahYz95Uxy0uLZ1+xnxrZ9IARXf1WDN8qCZjKhYCJtfQGm1NEU7qvgpMN83scz+4fbngjI2i4SSTfic4d4+/ZlZFhVwkJQGmpdHGrYBjWp37a1jY2tZMjQhQdcQwiFjRsm43a3D1zWqr3Y6o2ImpyppcRmHfirE2Dvsl/RXD6sfYey35uitA3fAhBHnsdAIKhNXQ7KwQf1Pn1XkJZ25GRQHzZYWNJsYbQzwmWJHfM3BN1pFC3omML9legA1eZ23SmAkyBXxu9CURRUVW17b92ur2sgKpRBZtQQVFVpM6hUk4KqKvj9AWqKfDTGbyIqrZBJkwSKoqIoJhRUQuUVhL74HiIK7kE3oZpMPJ/oZXnMBO561wNAXuNr7Ij7KactuxdLpGMSMftlcXzk2keMyc5oTwNDXLkop94CJjOoFlDNYDLed3wzn/kLd/BDUlKzGX7eTLRIhBXvfULQH+Hk836PalJZWVbPMyVlnDW4B/17GUmqGt8uJirFwbhTe7bpCmD5e8ZCxg+TNDafnsyU2GjGJbvaDMJ7du2jcskEALb2jaYizY5JE6RVBSisS2bnigPXoXhGTSXm+wXtO8wm5k3e0/Zn38a+DG4YzMyJO6jXVpO6aQhp1slgMrP+y08pDjaT5PGT+uAjqKqKyWRqe1/2nBFyWuNSKYrbQEp9LQ6niqVHJldNm9yptOY/3P9DOjs0/jtD6H97zc8//5whQ4YwderUTt+zK/l3xm9pfEgk3UwoEMFqP7gTUt+vUJbxRRnZr46Yjq5rBAJBFMWGqSVtt65pWC3m9pweQoCqtQycYKTdbPVIKPttdw5dF+iajh5pqYOi6S31UHRCWgCLXdlP3o41NDQthN3uxmQ2teX5MLwwrUmoBI3BJtzEgKIidA3hXkpm4skIoSNEGF0PU1tswazktdxXUNbkoznODDYTgbBOg7sZtbmaQYlqh/obuq63bTdUeYnRM4iyxiM03eiXbkS9tParsqoCkV5IUlohWdluEDpCaAiM91DAR31JMw0bhyJ0HcXWRMbE5WjLrJR834NVA/ys69fIIy/qJHrgjdMVfqfWkJoeA1oE9DBoYeP9MBQ3x/F+2YHrY1pRFBXFZMYWPQhXynS0iE6NFuEV1UvEomJpWSczuV6lNxbMLflJWgsYhoOGC+eN+BDFp6WgWFVsJrUtV4tf06j89jQAytLi2NnXeF6fLphFQfVgfhv9HGlLvZTHxwBQmZCLKzMDR1M19sZanA4HkUiIT3rvJJTupEoL0bduMCN1hTEjVxEJNJD4QQKOzVaIaAhNQ/d4aExM5Jvp09A0rcMan7ja4VgiMexOM/PmBGOcOHvDMno01h7x+T3eGTNmDFOmTOluMQ6KND4kEonkGODfSnqlRUBvMUj0SLtxokcQkRDu5jDCEY9qMmFVHahWFcVqwmQ2o6oHZmk96gTcYIvpUEU3GNGwHSRD7I+FruuGIRLREJqK2wSaAiEh8PoDxIcCWEzqAdN9B3v98FhnOJrt/tNrWSyWYzaRmqxqK5FIJMcA/9YgYTIbL+wHHFKA2KSjJtZ/hv3AwaQrDQ+gbdrMYjEWVDv2P+iw0bqgVnLsc/wHC0skEolEIjmukMaHRCKRSCSSLkUaHxKJRCKRSLoUaXxIJBKJRCLpUqTxIZFIJBKJpEuRxodEIpFIJJIuRRofEolEIpFIuhRpfEgkEolEIulSpPEhkUgkEomkS5HGh0QikUgkki5FGh8SiUQikUi6FGl8SCQSiUQi6VKk8SGRSCQSiaRLOeaq2gohAKM0r0QikUgkkuOD1nG7dRw/HMec8eHxeADIzMzsZkkkEolEIpH8u3g8HmJjYw/bRhGdMVG6EF3XKS8vJyYmBkVR/q1z3W43mZmZlJWV4XK5fiQJj3+kno6M1FHnkHrqHFJPnUPq6cgcyzoSQuDxeMjIyEBVD7+q45jzfKiqSs+ePf+ra7hcrmPuQzkWkXo6MlJHnUPqqXNIPXUOqacjc6zq6Egej1bkglOJRCKRSCRdijQ+JBKJRCKRdCknlPFhs9mYPXs2Nputu0U5ppF6OjJSR51D6qlzSD11DqmnI3Oi6OiYW3AqkUgkEonkxOaE8nxIJBKJRCI59pHGh0QikUgkki5FGh8SiUQikUi6FGl8SCQSiUQi6VJOGONj3bp1nHnmmcTFxZGYmMj1119Pc3Nz2/G6ujqmTp1KRkYGNpuNzMxMfv3rX/9P1ZA5ko42bNjAJZdcQmZmJg6HgwEDBvDkk092o8Tdw5H0BHDTTTcxcuRIbDYbw4YN6x5Bu5nO6Km0tJQZM2bgdDpJSUnhtttuIxKJdJPE3cPOnTuZOXMmSUlJuFwuTj31VL755psObb7++mvGjh1LTEwMaWlp3H777f9TeuqMjtasWcPpp59OXFwc8fHxTJkyhQ0bNnSTxN3DkfQ0b948FEU56Ku6urobJT+QE8L4KC8v54wzziAvL49Vq1axYMECtmzZwtVXX93WRlVVZs6cyccff8zOnTuZN28eX331FTfeeGP3Cd6FdEZHa9euJSUlhddff50tW7Zw9913c+edd/L00093n+BdTGf01Mq1117LRRdd1PVCHgN0Rk+apjFjxgxCoRArVqzglVdeYd68edx7773dJ3g3cNZZZxGJRFi0aBFr165l6NChnHXWWVRWVgKG0T99+nSmTp1KQUEB77zzDh9//DF33HFHN0vedRxJR83NzUydOpVevXqxatUqli1bRkxMDFOmTCEcDnez9F3HkfR00UUXUVFR0eE1ZcoUJkyYQEpKSjdL/wPECcDzzz8vUlJShKZpbfs2btwoAFFYWHjI85588knRs2fPrhCx2/lPdfTLX/5STJw4sStEPCb4d/U0e/ZsMXTo0C6U8NigM3r67LPPhKqqorKysq3Nc889J1wulwgGg10uc3dQU1MjAPHtt9+27XO73QIQCxcuFEIIceedd4pRo0Z1OO/jjz8WdrtduN3uLpW3O+iMjtasWSMAUVpa2tamM99fJxKd0dMPqa6uFhaLRbz66qtdJWanOSE8H8FgEKvV2qGQjcPhAGDZsmUHPae8vJwPPviACRMmdImM3c1/oiOApqYmEhISfnT5jhX+Uz39r9EZPa1cuZLBgweTmpra1mbKlCm43W62bNnStQJ3E4mJifTr149XX30Vr9dLJBLh+eefJyUlhZEjRwKGLu12e4fzHA4HgUCAtWvXdofYXUpndNSvXz8SExOZM2cOoVAIv9/PnDlzGDBgANnZ2d3bgS6iM3r6Ia+++ipOp5Of/exnXSztkTkhjI9JkyZRWVnJww8/TCgUoqGhoc1lWVFR0aHtJZdcgtPppEePHrhcLl566aXuELnL+Xd01MqKFSt45513uP7667tS1G7lP9HT/yKd0VNlZWUHwwNo+7vVTXyioygKX331FQUFBcTExGC323nsscdYsGAB8fHxgGGQrVixgrfeegtN09i3bx/3338/8L/xzHVGRzExMSxevJjXX38dh8NBdHQ0CxYs4PPPP8dsPubqo/4odEZPP2TOnDlceumlbT8MjiWOaePjjjvuOOTimdbX9u3bGTRoEK+88gqPPvooTqeTtLQ0cnJySE1NPaCs7+OPP866dev417/+xe7du7nlllu6qXdHhx9DRwCbN29m5syZzJ49m8mTJ3dDz44uP5aeTjSknjpHZ/UkhOBXv/oVKSkpLF26lNWrV3Puuedy9tlntxkWkydP5uGHH+bGG2/EZrPRt29fpk+fDnBc6/Jo6sjv9zNr1izGjRvHd999x/Lly8nPz2fGjBn4/f5u7ul/x9HU0/6sXLmSbdu2MWvWrG7o1ZE5ptOr19TUUFdXd9g2ubm5WK3Wtr+rqqqIiopCURRcLhdvv/02F1xwwUHPXbZsGePHj6e8vJz09PSjKntX8WPoaOvWrUycOJHrrruOBx544EeTvSv5sZ6l++67j48++oj169f/GGJ3OUdTT/feey8ff/xxB90UFRWRm5vLunXrGD58+I/VjR+dzupp6dKlTJ48mYaGhg7lz/v06cOsWbM6LCoVQlBRUUF8fDzFxcUMHDiQ1atXM3r06B+tHz8mR1NHc+bM4a677qKioqLNIAuFQsTHxzNnzhwuvvjiH7UvPyY/xrMEMGvWLNatW0dBQcGPIvd/yzHtr0pOTiY5OfnfOqfVrTt37lzsdjtnnnnmIdvqug4Yc67HK0dbR1u2bGHSpElcddVVJ4zhAT/+s3SicDT1NGbMGB544AGqq6vbVtovXLgQl8vFwIEDj67gXUxn9eTz+YADPRiqqrZ9/7SiKAoZGRkAvPXWW2RmZjJixIijJHHXczR15PP5UFUVRVE6HFcU5QA9Hm/8GM9Sc3Mz7777Lg8++ODRE/Ro052rXY8mf//738XatWvFjh07xNNPPy0cDod48skn245/+umnYu7cuWLTpk2iqKhIzJ8/XwwYMECMGzeuG6XuWo6ko02bNonk5GRx+eWXi4qKirZXdXUHCjrhAAACGUlEQVR1N0rd9RxJT0IIUVhYKAoKCsQNN9wg+vbtKwoKCkRBQcH/TBSHEEfWUyQSEfn5+WLy5Mli/fr1YsGCBSI5OVnceeed3Sh111JTUyMSExPF+eefL9avXy927Nghbr31VmGxWMT69evb2v3tb38TGzduFJs3bxb333+/sFgs4sMPP+w+wbuQzuho27ZtwmaziV/84hdi69atYvPmzeLyyy8XsbGxory8vJt70DV09lkSQoiXXnpJ2O120dDQ0D3CdoITxvi44oorREJCgrBarWLIkCEHhBYtWrRIjBkzRsTGxgq73S769Okjbr/99mP6wznaHElHs2fPFsABr6ysrO4RuJs4kp6EEGLChAkH1VVRUVHXC9xNdEZPxcXFYtq0acLhcIikpCTxu9/9ToTD4W6QtvtYs2aNmDx5skhISBAxMTHilFNOEZ999lmHNhMnTmz7bjr55JMPOH6i0xkdffnll2LcuHEiNjZWxMfHi0mTJomVK1d2k8TdQ2f0JIQQY8aMEZdeemk3SNh5juk1HxKJRCKRSE48jt+l1BKJRCKRSI5LpPEhkUgkEomkS5HGh0QikUgkki5FGh8SiUQikUi6FGl8SCQSiUQi6VKk8SGRSCQSiaRLkcaHRCKRSCSSLkUaHxKJRCKRSLoUaXxIJBKJRCLpUqTxIZFIJBKJpEuRxodEIpFIJJIuRRofEolEIpFIupT/B1+gphBZOoI/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in range(nTracts):  #optional full state visualization after squish\n",
    "    if t not in allCutVTDs and t not in skipList:\n",
    "        plotPoly(vtdGeom[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9715564f-3b60-43e5-9f1f-02f3dcee3933",
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 22  #pick a county for visualization if desired\n",
    "print(\"here are the faint(original) and squished shapes for county\",c)\n",
    "for t in countyTractList[c]:\n",
    "    plotPoly(vtdGeom[t])\n",
    "    plotPoly(tractGeom[t],0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "760bc48e-0236-4ad7-b3b8-d74795009f53",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"alternate simple approach for Florida Keys - translate all toward county CP\")\n",
    "c = 43\n",
    "vtdGeom = tractGeom.copy()  #a reset\n",
    "nTranslated = 0\n",
    "newCP = Point(-81, 25.1)\n",
    "for v in countyTractList[c]:\n",
    "    if clipPoly.contains(tractCP[v]):\n",
    "        xDelta, yDelta = newCP.x - tractCP[v].x, newCP.y - tractCP[v].y\n",
    "        xOFF, yOFF = 0.95 * xDelta, 0.95 * yDelta\n",
    "        vtdGeom[v] = translate(vtdGeom[v],xoff= xOFF, yoff=yOFF)\n",
    "        nTranslated +=1\n",
    "print(\"I translated\",nTranslated,\"vtds toward the center of county\",c)\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]\n",
    "countyGeom[c] = vtdGeom[countyTractList[c][0]]\n",
    "for v in countyTractList[c]:\n",
    "    countyGeom[c] = countyGeom[c].union(vtdGeom[v])\n",
    "    plotPoly(hdCP[v].buffer(0.03))\n",
    "plotPoly(countyGeom[c])\n",
    "unsquishedMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "#plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4ef91f8f-dabb-4c58-a8a4-bba8e725e586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on confirming HD center 0 is inside the map's convex hull\n",
      "working on confirming HD center 500 is inside the map's convex hull\n",
      "working on confirming HD center 1000 is inside the map's convex hull\n",
      "working on confirming HD center 1500 is inside the map's convex hull\n",
      "working on confirming HD center 2000 is inside the map's convex hull\n",
      "working on confirming HD center 2500 is inside the map's convex hull\n",
      "working on confirming HD center 3000 is inside the map's convex hull\n",
      "working on confirming HD center 3500 is inside the map's convex hull\n",
      "working on confirming HD center 4002 is inside the map's convex hull\n",
      "working on confirming HD center 4502 is inside the map's convex hull\n",
      "working on confirming HD center 5002 is inside the map's convex hull\n",
      "working on confirming HD center 5502 is inside the map's convex hull\n",
      "working on confirming HD center 6002 is inside the map's convex hull\n",
      "working on confirming HD center 6502 is inside the map's convex hull\n",
      "working on confirming HD center 7002 is inside the map's convex hull\n",
      "Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 - draw polygonal HDs.  #REQUIRES CONSISTENT TREATMENT OF CCB'S \n",
    "#For GA, MA, MD, MN, NC we draw HDs for ALL vtds, even if they are in a CCB.  We use the clipPoly's to squish in the corners for these HD shapes\n",
    "#Not sure if below would work if we have cut districts AND squished-in corners\n",
    "#We normally draw for each (squished or orig) vtd.  Or, read in tract or blockgroup geometries, use those pops and unit centerpoints\n",
    "\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]  #remember, this is after any squish operation\n",
    "print(\"Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\")\n",
    "useSquish = int(input(\"enter 1 to use squished shapes (e.g. for MD, MN), enter 0 for unclipped states\"))\n",
    "if useSquish == 1:\n",
    "    convexMAP = hdCP[countyTractList[uncutCountyList[0]][0]].buffer(0.1) \n",
    "    for v in range(nTracts):\n",
    "        if v not in skipList and v not in allCutVTDs:\n",
    "            convexMAP = convexMAP.union(hdCP[v].buffer(0.1))\n",
    "else:  #build the map via simple union of counties not wholly in fully cut-out districts\n",
    "    convexMAP = countyGeom[uncutCountyList[0]]\n",
    "    for c in uncutCountyList:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "    #convexMAP = MAP.centroid\n",
    "    #for c in range(nCounties):\n",
    "    #    if c not in allFusedCounties:\n",
    "    #        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if t not in allCutVTDs and t not in skipList:  #keep low-pop tracts as VEST may have assigned voters to them\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on confirming HD center\",t,\"is inside the map's convex hull\")\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8393e96a-75c6-48ec-94e8-1f6fe58d31df",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = nTracts  #need to run this if we start option 2 from a vest list, not a previously run HD poly list\n",
    "HDcountyNo = countyNo.copy()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature equivalency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bcaf6ea2-1c3b-48c1-9ad6-937d7b7e4385",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\n",
      "working on tract-tract distances for unit 0 out of 7059 . Time = 0\n",
      "working on tract-tract distances for unit 400 out of 7059 . Time = 178\n",
      "working on tract-tract distances for unit 800 out of 7059 . Time = 346\n",
      "working on tract-tract distances for unit 1200 out of 7059 . Time = 503\n",
      "working on tract-tract distances for unit 1600 out of 7059 . Time = 651\n",
      "working on tract-tract distances for unit 2000 out of 7059 . Time = 786\n",
      "working on tract-tract distances for unit 2400 out of 7059 . Time = 916\n",
      "working on tract-tract distances for unit 2800 out of 7059 . Time = 1030\n",
      "working on tract-tract distances for unit 3200 out of 7059 . Time = 1111\n",
      "working on tract-tract distances for unit 3601 out of 7059 . Time = 1184\n",
      "working on tract-tract distances for unit 4002 out of 7059 . Time = 1247\n",
      "working on tract-tract distances for unit 4402 out of 7059 . Time = 1299\n",
      "working on tract-tract distances for unit 4802 out of 7059 . Time = 1359\n",
      "working on tract-tract distances for unit 5202 out of 7059 . Time = 1410\n",
      "working on tract-tract distances for unit 5602 out of 7059 . Time = 1458\n",
      "working on tract-tract distances for unit 6002 out of 7059 . Time = 1497\n",
      "working on tract-tract distances for unit 6402 out of 7059 . Time = 1519\n",
      "working on tract-tract distances for unit 6802 out of 7059 . Time = 1531\n",
      "All done; total elapsed  1533 seconds for WI with 8 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "our maxD was 5.000443356135309\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT, despite the \"unit\" nomenclature\n",
    "print(\"Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default: too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if nDistricts < 10: #closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "else:\n",
    "    for c in uncutCountyList:\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in uncutCountyList:\n",
    "                if cc in neighborCountyList[c]:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "                else:    \n",
    "                    dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                    if dist < closeCountyDist:\n",
    "                        closeCountyList[c].append(cc)\n",
    "                        closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "\n",
    "for i,t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on tract-tract distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()\n",
    "print(\"our maxD was\",maxD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2f392acb-ba52-4343-80ae-a58ba0b57366",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 7059 . Time = 0\n",
      "working on unit-unit angles for unit 400 out of 7059 . Time = 79\n",
      "working on unit-unit angles for unit 800 out of 7059 . Time = 149\n",
      "working on unit-unit angles for unit 1200 out of 7059 . Time = 215\n",
      "working on unit-unit angles for unit 1600 out of 7059 . Time = 283\n",
      "working on unit-unit angles for unit 2000 out of 7059 . Time = 344\n",
      "working on unit-unit angles for unit 2400 out of 7059 . Time = 396\n",
      "working on unit-unit angles for unit 2800 out of 7059 . Time = 445\n",
      "working on unit-unit angles for unit 3200 out of 7059 . Time = 490\n",
      "working on unit-unit angles for unit 3601 out of 7059 . Time = 530\n",
      "working on unit-unit angles for unit 4002 out of 7059 . Time = 565\n",
      "working on unit-unit angles for unit 4402 out of 7059 . Time = 599\n",
      "working on unit-unit angles for unit 4802 out of 7059 . Time = 626\n",
      "working on unit-unit angles for unit 5202 out of 7059 . Time = 654\n",
      "working on unit-unit angles for unit 5602 out of 7059 . Time = 673\n",
      "working on unit-unit angles for unit 6002 out of 7059 . Time = 688\n",
      "working on unit-unit angles for unit 6402 out of 7059 . Time = 698\n",
      "working on unit-unit angles for unit 6802 out of 7059 . Time = 704\n",
      "All done with angles; total elapsed seconds = 705\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 \n",
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for i, t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "#plt.hist(uuAngle)\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4cc54eba-ca37-4680-9699-37332133afb8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "736714.75 8 5893718.0 8.0 5893718.0\n",
      "5893718.0 5893718 1.0\n"
     ]
    }
   ],
   "source": [
    "print(r3(aDP), nDistricts, statePop, statePop/aDP, trueStatePop)\n",
    "HDweight = [0 for t in range(nHDs)]\n",
    "for t in populatedTractList:\n",
    "    HDweight[t] = tractPop[t] / trueStatePop #skipping the cutList tracts\n",
    "print(statePop,np.sum([tractPop[t] for t in populatedTractList]), r5(np.sum(HDweight))) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "9fc17acc-9afa-4496-a94d-c2b2049b743a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eliminating WA ferry neighbors 4-27\n",
      "15s nbrs = [4, 13, 14, 17, 22, 27] 27s nbrs = [14, 15, 28, 36]\n",
      "eliminating WA ferry neighbors 15-27\n"
     ]
    }
   ],
   "source": [
    "#print(\"4s nbrs =\",neighborCountyList[4], \"27s nbrs =\",neighborCountyList[27])\n",
    "if STATE == \"WA\":\n",
    "    print(\"eliminating WA ferry neighbors 4-27\")\n",
    "    #neighborCountyList[4].remove(27)\n",
    "    ##neighborCountyList[27].remove(4)\n",
    "print(\"15s nbrs =\",neighborCountyList[15], \"27s nbrs =\",neighborCountyList[27])\n",
    "if STATE == \"WA\":\n",
    "    print(\"eliminating WA ferry neighbors 15-27\")\n",
    "    neighborCountyList[15].remove(27)\n",
    "    neighborCountyList[27].remove(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "dac2348a-060a-40a9-beeb-02ff70ec1aa1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\n"
     ]
    }
   ],
   "source": [
    "print(\"RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\")\n",
    "opt2nbrCtyList = [neighborCountyList[c].copy() for c in range(nCounties)]\n",
    "for i in range(nClips):\n",
    "    cList = toSquishCountiesList[i]\n",
    "    for c in cList:\n",
    "        for cc in cList:\n",
    "            for ccc in neighborCountyList[cc]:\n",
    "                if ccc not in opt2nbrCtyList[c] and ccc != c:\n",
    "                    opt2nbrCtyList[c].append(ccc)\n",
    "#for c in range(nCounties):\n",
    "#    for cc in opt2nbrCtyList[c]:\n",
    "#        plotPoly(countyGeom[cc])\n",
    "#    plotCenter(c,countyGeom[c])\n",
    "#    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3873aaa2-0c39-4ac0-99c3-92dd7c18c555",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 668.127 of targetWedgePop\n",
      "I am working on HD number 0 of 7059 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 400 of 7059 HDs.  Elapsed sec = 104\n",
      "I am working on HD number 800 of 7059 HDs.  Elapsed sec = 176\n",
      "I am working on HD number 1200 of 7059 HDs.  Elapsed sec = 251\n",
      "I am working on HD number 1600 of 7059 HDs.  Elapsed sec = 331\n",
      "I am working on HD number 2000 of 7059 HDs.  Elapsed sec = 411\n",
      "I am working on HD number 2400 of 7059 HDs.  Elapsed sec = 489\n",
      "I am working on HD number 2800 of 7059 HDs.  Elapsed sec = 561\n",
      "I am working on HD number 3200 of 7059 HDs.  Elapsed sec = 642\n",
      "I am working on HD number 3601 of 7059 HDs.  Elapsed sec = 734\n",
      "I am working on HD number 4002 of 7059 HDs.  Elapsed sec = 813\n",
      "I am working on HD number 4402 of 7059 HDs.  Elapsed sec = 888\n",
      "I am working on HD number 4802 of 7059 HDs.  Elapsed sec = 972\n",
      "I am working on HD number 5202 of 7059 HDs.  Elapsed sec = 1037\n",
      "I am working on HD number 5602 of 7059 HDs.  Elapsed sec = 1125\n",
      "I am working on HD number 6002 of 7059 HDs.  Elapsed sec = 1204\n",
      "I am working on HD number 6402 of 7059 HDs.  Elapsed sec = 1296\n",
      "I am working on HD number 6802 of 7059 HDs.  Elapsed sec = 1365\n",
      "1409.403 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\n",
      "vtd avg and sd usage are 1.00002 0.13149\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/len(populatedTractList)\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",r3(tolerPops[0]),\"of targetWedgePop\")\n",
    "tractPrintInterval = 400  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "for t in populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "\n",
    "for kkkj, t in enumerate(populatedTractList):  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (kkkj % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    opt2nbrCtyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in populatedTractList],[HDvPop[t] for t in populatedTractList] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b7f36a0f-a3c6-4b07-aecd-9e010b02918f",
   "metadata": {},
   "outputs": [],
   "source": [
    "DATE = \"19May\"  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "37c238bb-b340-431b-ad11-95e4409d9699",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the polygon-based results to a file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (i.e. generating polygonal HDs from scratch)\n",
    "print(\"Now we will write the polygon-based results to a file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "hdCPx, hdCPy =   [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea, \"countyNo\":countyNo,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList} ) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"convexHD2_\"+str(int(nDistricts))+\"nW4_\"+DATE+\".csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "075013a3-f3ee-4a44-ac4a-27a7492e027a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./2024state_HD_output/WI7059convexHD2_8nW4_19May.csv\n"
     ]
    }
   ],
   "source": [
    "print(\"./\"+outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6e7e8ccd-8e11-4d6d-970d-b059401e0a3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the original HD polygon shape assignment csv, e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv ./2024state_HD_output/WI7059convexHD2_8nW4_19May.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have read back in the original HD shapes\n",
      "Ready to capture unit centroids based on these HD poly shapes; see next block\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 --> 1 - we already have an ensemble of HDpoly's and their weights (from running option 2 above)\n",
    "#read them in\n",
    "#determine each cluster's required area fraction capture to get 1.00 cluster use across the HD set\n",
    "#then determine total pop (including cluster in/out) for each HD, and total unit use\n",
    "#then move into triage\n",
    "infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                   \"e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "shapeDF = pd.read_csv(infilename)\n",
    "HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "HDarea = shapeDF['HDarea'].to_list()\n",
    "#tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "nHDs = len(shapeDF)\n",
    "hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "hdCPy = shapeDF['centroid y'].to_list()\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "HDradius0 = shapeDF['HDradius0'].to_list()\n",
    "HDradius1 = shapeDF['HDradius1'].to_list()\n",
    "HDradius2 = shapeDF['HDradius2'].to_list()\n",
    "HDradius3 = shapeDF['HDradius3'].to_list()\n",
    "HDangle0 = shapeDF['HDangle0'].to_list()\n",
    "HDangle1 = shapeDF['HDangle1'].to_list()\n",
    "HDangle2 = shapeDF['HDangle2'].to_list()\n",
    "HDangle3 = shapeDF['HDangle3'].to_list()\n",
    "HDradius, HDangle = list(), list()\n",
    "for t in range(nHDs):\n",
    "    HDradius.append( [HDradius0[t],HDradius1[t],HDradius2[t],HDradius3[t] ] )\n",
    "    HDangle.append(  [HDangle0[t], HDangle1[t], HDangle2[t], HDangle3[t]  ] )\n",
    "print(\"I have read back in the original HD shapes\")\n",
    "popHDlist = list()\n",
    "HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)\n",
    "        HDpoly[t] = buildArcPoly(hdCP[t],HDradius[t], HDangle[t], xScale)\n",
    "if \"countyNo\" in shapeDF.columns.values:  #\"pigs\" == \"can fly\":\n",
    "    HDcountyNo = shapeDF['countyNo'].to_list()\n",
    "else:\n",
    "    print(\"County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\")\n",
    "    HDcountyNo = [-999]*nHDs\n",
    "    for t in popHDlist:\n",
    "        for c, geom in enumerate(countyGeom):\n",
    "            if geom.contains(hdCP[t]):\n",
    "                HDcountyNo[t] = c\n",
    "                break\n",
    "    unassignedList = list()\n",
    "    for t in popHDlist:\n",
    "        if HDcountyNo[t] == -999:\n",
    "            unassignedList.append(t)\n",
    "    if len(unassignedList) > 0:\n",
    "        print(\"I found\",len(unassignedList),\"populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\")\n",
    "        for t in unassignedList:\n",
    "            minDist = maxD\n",
    "            for c in range(nCounties):\n",
    "                dist = countyGeom[c].distance(hdCP[t])\n",
    "                if dist < minDist:\n",
    "                    minDist = dist\n",
    "                    HDcountyNo[t] = c\n",
    "    if len(unassignedList) > 0:\n",
    "        if len(unassignedList) > 20:\n",
    "            print(\"  (too many to plot individually)\")\n",
    "        else:\n",
    "            print(\"FYI, here are those manually assigned HDcenters to their counties\")\n",
    "            for t in unassignedList:\n",
    "                print(t,HDweight[t],\" is the HD row and its weight in the ensemble\")\n",
    "                plotPoly(hdCP[t].buffer(0.1))\n",
    "                plotCenter(int(HDvPop[t]),hdCP[t],6)\n",
    "                plotPoly(countyGeom[HDcountyNo[t]])\n",
    "                plotPoly(MAP,0.2)\n",
    "                plt.show()\n",
    "print(\"Ready to capture unit centroids based on these HD poly shapes; see next block\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3f0f8434-5f7a-41d1-bd86-07ec230b4aef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, let me renormalize the HDweights if there were cut districts\n",
      "our HDweight sum was 0.9999999999997904 but is now 1.0\n"
     ]
    }
   ],
   "source": [
    "print(\"now, let me renormalize the HDweights if there were cut districts\")\n",
    "sumWt = np.sum(HDweight)\n",
    "HDweight = [HDweight[t]/sumWt for t in range(nHDs) ]\n",
    "\n",
    "print(\"our HDweight sum was\",sumWt,\"but is now\",np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af22eba0-8e05-43e7-b96b-6aedab016957",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see early states for continuing w/option 1.  NC and later use option 3 ....\n",
    "# ****if this is a cold restart, would need to read in unit topology before below block  **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8d5f678f-c2df-4ee7-bafe-fd75ba2cb42e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\n"
     ]
    }
   ],
   "source": [
    "#OPTION 3 \n",
    "print(\"lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\")\n",
    "HDtractListString = shapeDF[\"HDtractList\"]\n",
    "HDtractList = [ast.literal_eval(HDtractListString[t]) for t in range(nHDs)]\n",
    "nCCBs = len(CCBlist)\n",
    "CCBpopFrac = [[0. for j in range(nCCBs) ]  for t in range(nHDs)]\n",
    "\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ec034144-b3dc-4b72-9350-6d85cabcb8a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\n",
      "working on vtd --> unit conversion for HD 1 last HD had pop 736524.467\n",
      "working on vtd --> unit conversion for HD 1001 last HD had pop 689292.896\n",
      "working on vtd --> unit conversion for HD 2001 last HD had pop 737129.0\n",
      "working on vtd --> unit conversion for HD 3001 last HD had pop 736760.118\n",
      "working on vtd --> unit conversion for HD 4001 last HD had pop 736306.805\n",
      "working on vtd --> unit conversion for HD 5001 last HD had pop 737301.039\n",
      "working on vtd --> unit conversion for HD 6001 last HD had pop 736459.767\n",
      "working on vtd --> unit conversion for HD 7001 last HD had pop 609455.85\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\" )\n",
    "HDunitList = [ list() for t in range(nHDs) ]\n",
    "for t in range(nHDs):\n",
    "    if t %1000 == 1:\n",
    "        print(\"working on vtd --> unit conversion for HD\",t,\"last HD had pop\",r3( np.sum([unitPop[u] for u in HDunitList[t-1]]) ) )\n",
    "    capturedCountyPop = [0. for c in range(nCounties)]\n",
    "    capturedCCBpop = [0. for i in range(nCCBs)]\n",
    "    for v in HDtractList[t]:\n",
    "        c = HDcountyNo[v]\n",
    "        if c in range(nCounties):  #we assigned countyno = -999 to unpopulated tracts\n",
    "            if c in unitCounties:\n",
    "                capturedCountyPop[c] += tractPop[v]\n",
    "            elif c in allFusedCounties:\n",
    "                for i, L in enumerate(CCBlist):\n",
    "                    if c in L:\n",
    "                        capturedCCBpop[i] += tractPop[v]\n",
    "            else:  #this vtd not part of a unit or fused county.  Could be split into fragments\n",
    "                for u in countyUnitList[c]:\n",
    "                    if unitParentVTDno[u] == v :  #we assign all units = vtd fragments from this HDTL-captured vtd\n",
    "                        HDunitList[t].append(u)\n",
    "    for c in unitCounties:\n",
    "        if capturedCountyPop[c] > 0.5 * countyPop[c]:\n",
    "            HDunitList[t].append(allUnits.index(c+0.5))\n",
    "    for i in range(nCCBs):  #don't yet assign in/out CCBs.  We'll do so in below block.  Just update max possible use for each CCB\n",
    "        CCBpopFrac[t][i] = capturedCCBpop[i] / CCBpop[i]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "1494814c-7b90-425c-b8b1-3a2006bdeb2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\n",
      "CCBno 0 with pop 13737.0 would be used 1.202 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 1 with pop 169151.0 would be used 2.272 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 2 with pop 171003.0 would be used 1.764 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 3 with pop 92501.0 would be used 2.049 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 4 with pop 51938.0 would be used 1.577 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n"
     ]
    },
    {
     "data": {
      "image/png": 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vyM7Otr+2bdsGwAMPPADAk08+yV//+lfWr1/Pl19+SVZWFuPGjbMfX1VVxZgxY6isrGTXrl388Y9/5J133uGZZ55x4imJiIhIW+dQQAkNDSUiIsL+2rhxIz179uTOO++ksLCQ1atX89JLLzFixAgGDhzImjVr2LVrF7t37wbgs88+4+jRo7z77rsMGDCAe+65h+eff560tDTNsyEiIiJ2TR6DUllZybvvvsujjz6Ki4sLGRkZWCwW+9wbULOoXbdu3UhPTwcgPT2d/v37Ex4ebi+TkJBAUVERR44cabCtiooKioqK6rxERESk/WpyQPn4448pKCjgkUceAcBsNuPp6UlgYGCdcuHh4ZjNZnuZH4eT2v21+xqSmppKQECA/RUVpSdxRERE2rMmB5TVq1dzzz33EBkZ6cz+1Gv+/PkUFhbaX2fPnm32NkVERKT1NGkelH/84x9s376dDRs22LdFRERQWVlJQUFBnbsoOTk5RERE2Mvs3bu3Tl21T/nUlqmPl5cXXl5eTelqHdkl2eRX5F93PY0R5BWEyc/UIm2JiIi0N00KKGvWrCEsLIwxY8bYtw0cOBAPDw927NhBYmIiAMePH+fMmTP2xe7i4+NJSUkhNzeXsLAwALZt24a/vz9xcXHXey5XlV2SzdhPxlJmLWvWdmr5uPvwydhPHAopZrOZlJQUNm3axLlz5wgLC2PAgAHMnj2bu+++217uwIEDLF26lJ07d1JYWEhUVBR33XUXycnJxMbGcvr0aaKjo+3lPTw86NatG4888ghPP/00Li4u9bb/97//nWXLlvH1119z4cIFevToweOPP85vfvObpl8IERGRJnA4oFRXV7NmzRomTZqEu/u/Dg8ICGDKlCnMmTOH4OBg/P39mTVrFvHx8QwdOhSAUaNGERcXx0MPPcTy5csxm80sWLCApKQkp9whuZr8inzKrGWk3pFKTEBMs7aVWZjJ/K/mk1+R3+iAcvr0aYYNG0ZgYCArVqygf//+WCwWtm7dSlJSEt9++y0AGzduJDExkYSEBN577z169uxJbm4u69evZ+HChaxbt85e5/bt2+nXrx8VFRV8/fXXTJ06FZPJxJQpU+rtQ0ZGBmFhYbz77rtERUWxa9cupk2bhpubGzNnzrz+CyMiItJIDgeU7du3c+bMGR599NEr9r388su4urqSmJhIRUUFCQkJvPHGG/b9bm5ubNy4kenTpxMfH4+vry+TJk1i8eLF13cWDogJiCEupHnv1jTFjBkzcHFxYe/evfj6+tq39+vXz36tL126xOTJkxk9ejQfffSRvUx0dDRDhgyhoKCgTp0hISH2r866d+/OmjVr2L9/f4MB5fJ/05iYGNLT09mwYYMCioiItCiHA8qoUaMaXCnX29ubtLQ00tLSGjy+e/fubN682dFm27W8vDy2bNlCSkpKnXBSq3ZMz9atW7lw4QJz586tt57Ln6D6sX379pGRkcHDDz/sUN8KCwsJDg526BgREZHr1bEWCzSokydPYrPZ6NOnz1XLfffddwDXLFfrtttuw9XVlcrKSiwWC9OmTXMooOzatYt169axadOmRh8jIiLiDAooBtDQHammlqu1bt06+vbti8Vi4fDhw8yaNYugoCCWLVt2zWMPHz7M2LFjefbZZxk1apRD7YqIiFwvrWZsAL1798bFxcU+ELYhsbGxANcsVysqKopevXrRt29fHnjgAWbPns2LL75IeXn5VY87evQod999N9OmTWPBggWNOwkREREnUkAxgODgYBISEkhLS6O0tPSK/bWDX0eNGkWXLl1Yvnx5vfVcPkj2cm5ublit1quue3TkyBGGDx/OpEmTSElJafQ5iIiIOJMCikGkpaVRVVXF4MGD+fDDD/nuu+84duwYr732mn0eGV9fX95++202bdrE/fffz/bt2zl9+jT79u1j7ty5PP7443XqvHjxImazmR9++IFPP/2UV199leHDh+Pv719vHw4fPszw4cMZNWoUc+bMwWw2YzabOX/+fLOfv4iIyI91uDEomYWZhmwjJiaG/fv3k5KSwlNPPUV2djahoaEMHDiQVatW2cuNHTuWXbt2kZqayoQJEygqKiIqKooRI0awZMmSOnXWLtzo5uaGyWRi9OjRV70r8pe//IXz58/z7rvv8u6779q3d+/endOnTzt8TiIiIk3VYQJKkFcQPu4+zP9qfou05+PuQ5BXkEPHmEwmVq5cycqVK69abtCgQXz44YcN7u/Ro4fDA2oBFi1axKJFixw+TkRExNk6TEAx+Zn4ZOwnWotHRESkDegwAQVqQopCg4iIiPFpkKyIiIgYjgKKiIiIGE6H+opHRETEcArOwqWLrdN2pxAIjGqdtq9BAUVERKS1FJyFtMFgudQ67Xt0gqS9hgwpCigiIiKt5dLFmnAy7i3oEtuybV84ARseq+mDAoqIiIhcoUssRA5o7V4YigbJioiIiOF0qDsolqwsrPktM1Gbe1AQHpGRLdKWiIhIe9NhAoolK4vvx9yLraysRdpz8fGh56aNDoUUs9lMSkoKmzZt4ty5c4SFhTFgwABmz57N3XffbS934MABli5dys6dOyksLCQqKoq77rqL5ORkYmNjOX36NNHR0fbyHh4edOvWjUceeYSnn34aFxeXetu/ePEiEydO5H//93+5ePEiYWFhjB07lqVLlza4wKCIiEhz6DABxZqfj62sjMgVy/GMiWnWtiozM8lKnos1P7/RAeX06dMMGzaMwMBAVqxYQf/+/bFYLGzdupWkpCS+/fZbADZu3EhiYiIJCQm899579OzZk9zcXNavX8/ChQtZt26dvc7t27fTr18/Kioq+Prrr5k6dSomk4kpU6bU2wdXV1fGjh3LkiVLCA0N5eTJkyQlJZGXl8fatWuv/8KIiIg0UocJKLU8Y2Lw6devtbtxhRkzZuDi4sLevXvx9fW1b+/Xrx+PPvooAJcuXWLy5MmMHj2ajz76yF4mOjqaIUOGUFBQUKfOkJAQIiIigJoVidesWcP+/fsbDChBQUFMnz7d/r579+7MmDGDFStWOOs0RUREGkWDZA0gLy+PLVu2kJSUVCec1AoMDARg69atXLhwgblz59ZbT225+uzbt4+MjAyGDBnS6H5lZWWxYcMG7rzzzkYfIyIi4gwKKAZw8uRJbDYbffr0uWq57777DuCa5Wrddttt+Pn54enpya233sovf/lLHn744Wse96tf/YpOnTrRtWtX/P39efvttxvVnoiIiLMooBiAzWZzarla69at4+DBg/z973/ngw8+4JNPPmHevHnXPO7ll19m//79fPLJJ3z//ffMmTPHoXZFRESuV4cbg2JEvXv3xsXFxT4QtiGxsTWzDH777bfEx8dfs96oqCh69eoFQN++ffn+++9ZuHAhixYtwtvbu8HjIiIiiIiIoE+fPgQHB3PHHXewcOFCTCaTA2clIiLSdLqDYgDBwcEkJCSQlpZGaWnpFftrB7+OGjWKLl26sHz58nrruXyQ7OXc3NywWq1UVlY2um/V1dUAVFRUNPoYERGR66U7KAaRlpbGsGHDGDx4MIsXL+bmm2/GarWybds2Vq1axbFjx/D19eXtt9/mgQce4P777+eJJ56gV69eXLhwgQ8++IAzZ87w/vvv2+u8ePEiZrMZq9XKoUOHePXVVxk+fHiDc5ps3ryZnJwcbr31Vvz8/Dhy5AjJyckMGzaMHj16tNCVEBER6YABpTIz05BtxMTEsH//flJSUnjqqafIzs4mNDSUgQMHsmrVKnu5sWPHsmvXLlJTU5kwYQJFRUVERUUxYsQIlixZUqfOkSNHAjV3TkwmE6NHjyYlJaXBPvj4+PDWW2/x5JNPUlFRQVRUFOPGjWvUuBURERFn6jABxT0oCBcfH7KS639E19lcfHxwDwpy6BiTycTKlStZuXLlVcsNGjSIDz/8sMH9PXr0cHhALcDw4cPZtWuXw8eJiIg4W4cJKB6RkfTctFFr8YiIiLQBHSagQE1IUWgQERExPj3FIyIiIoajgCIiIiKGo4AiIiIihqOAIiIiIobjcEA5d+4cv/71rwkJCcHHx4f+/fuzb98++36bzcYzzzyDyWTCx8eHkSNH2he5q5WXl8fEiRPx9/cnMDCQKVOmUFJScv1nIyIiIu2CQwElPz+fYcOG4eHhwaeffsrRo0d58cUXCfrRfB/Lly/ntdde480332TPnj34+vqSkJBAeXm5vczEiRM5cuQI27ZtY+PGjezcuZNp06Y576xERESkTXPoMeMXXniBqKgo1qxZY98WHR1t/7vNZuOVV15hwYIFjB07FoA//elPhIeH8/HHHzN+/HiOHTvGli1b+Oabbxg0aBAAr7/+OqNHj+b3v/89kXoMWEREpMNzKKD893//NwkJCTzwwAN8+eWXdO3alRkzZvDYY48BcOrUKcxms32KdYCAgACGDBlCeno648ePJz09ncDAQHs4gZop2V1dXdmzZw+/+MUvrmi3oqKizmJ1RUVFDp8oQHFeOeUlliYd6yhvPw86Bze8YrCIiIg0zKGAkpmZyapVq5gzZw6/+93v+Oabb3jiiSfw9PRk0qRJmM1mAMLDw+scFx4ebt9nNpsJCwur2wl3d4KDg+1lLpeamspzzz3nSFevUJxXztpFu7FWVl9XPY3l7unKhEVDHQopZrOZlJQUNm3axLlz5wgLC2PAgAHMnj2bu+++217uwIEDLF26lJ07d1JYWEhUVBR33XUXycnJxMbGcvr06Tp3tjw8POjWrRuPPPIITz/9NC4uLtfsy8WLF7nllls4d+4c+fn5BAYGOnT+IiIi18OhgFJdXc2gQYNYunQpAD/5yU84fPgwb775JpMmTWqWDgLMnz+fOXPm2N/XLpDniPISC9bKakZOjiPY5OvsLtaRl13K9jVHKS+xNDqgnD59mmHDhhEYGMiKFSvo378/FouFrVu3kpSUxLfffgvAxo0bSUxMJCEhgffee4+ePXuSm5vL+vXrWbhwIevWrbPXuX37dvr160dFRQVff/01U6dOxWQyMWXKlGv2Z8qUKdx8882cO3euaRdBRETkOjgUUEwmE3FxcXW29e3b175wXUREBAA5OTmYTCZ7mZycHAYMGGAvk5ubW6cOq9VKXl6e/fjLeXl54eXl5UhXGxRs8iW0W2en1OVMM2bMwMXFhb179+Lr+68A1a9fPx599FEALl26xOTJkxk9ejQfffSRvUx0dDRDhgyhoKCgTp0hISH2a9q9e3fWrFnD/v37rxlQVq1aRUFBAc888wyffvqpk85QRESk8Rx6imfYsGEcP368zrYTJ07QvXt3oOaDMiIigh07dtj3FxUVsWfPHuLj4wGIj4+noKCAjIwMe5nPP/+c6upqhgwZ0uQTacvy8vLYsmULSUlJdcJJrdqvV7Zu3cqFCxeYO7f+FZmv9jXMvn37yMjIuOY1Pnr0KIsXL+ZPf/oTrq6aJkdERFqHQ3dQnnzySW677TaWLl3KL3/5S/bu3csf/vAH/vCHPwDg4uLC7NmzWbJkCb179yY6OpqFCxcSGRnJz3/+c6DmjsvPfvYzHnvsMd58800sFgszZ85k/PjxHfYJnpMnT2Kz2ejTp89Vy9XOJ3OtcrVuu+02XF1dqaysxGKxMG3aNB5++OEGy1dUVPCrX/2KFStW0K1bNzIzMxt/EiIiIk7kUEC59dZb+eijj5g/fz6LFy8mOjqaV155hYkTJ9rLzJ07l9LSUqZNm0ZBQQG33347W7Zswdv7X2Mx3nvvPWbOnMndd9+Nq6sriYmJvPbaa847qzbGZrM5tVytdevW0bdvXywWC4cPH2bWrFkEBQWxbNmyesvPnz+fvn378utf/9qhdkRERJzNoYACcO+993Lvvfc2uN/FxYXFixezePHiBssEBwezdu1aR5tut3r37o2Li4t9IGxDYmNjAfj222/tX5ldTVRUFL169QJq7lx9//33LFy4kEWLFtUJjLU+//xzDh06xF/+8hfgX4GoS5cuPP3009f9JJWIiEhjaZCBAQQHB5OQkEBaWhqlpaVX7K8d/Dpq1Ci6dOnC8uXL663n8kGyl3Nzc8NqtVJZWVnv/g8//JC///3vHDx4kIMHD/L2228D8NVXX5GUlNT4ExIREblODt9BkeaRlpbGsGHDGDx4MIsXL+bmm2/GarWybds2Vq1axbFjx/D19eXtt9/mgQce4P777+eJJ56gV69eXLhwgQ8++IAzZ87w/vvv2+u8ePEiZrMZq9XKoUOHePXVVxk+fDj+/v719qFnz5513l+4cAGoufuieVBERKQldbiAkpd95R0KI7QRExPD/v37SUlJ4amnniI7O5vQ0FAGDhzIqlWr7OXGjh3Lrl27SE1NZcKECfY5YUaMGMGSJUvq1Fk7o6+bmxsmk4nRo0eTkpJyfScnIiLSAjpMQPH288Dd05Xta462SHvunq54+3k4dIzJZGLlypWsXLnyquUGDRpkn3umPj169HB4QG197rrrLqfUIyIi4qgOE1A6B3szYdFQrcUjIiLSBnSYgAI1IUWhQURExPj0FI+IiIgYjgKKiIiIGI4CioiIiBhOuw0oevqkZeg6i4hIc2h3g2Q9PGoe7b106RI+Pj6t3Jv2r3ZWWjc3t1buiYi0BZasLKz5+a3StntQEB4ddFHatqjdBRQ3NzcCAwPJzc0FoFOnTri4uLRyr9qn6upqzp8/T6dOnXB3b3c/SiLiZJasLL4fcy+2srJWad/Fx4eemzYqpLQR7fJTJSIiAsAeUqT5uLq60q1bN4VAEbkma34+trIyIlcsxzMmpkXbrszMJCt5Ltb8fAWUNqJdBhQXFxdMJhNhYWFYLC0zMVtH5enpiatrux3KJCLNwDMmBp9+/Vq7G2Jw7TKg1HJzc9PYCBERkTZI/+srIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIobjUEBZtGgRLi4udV59+vSx7y8vLycpKYmQkBD8/PxITEwkJyenTh1nzpxhzJgxdOrUibCwMJKTk7Farc45GxEREWkX3B09oF+/fmzfvv1fFbj/q4onn3ySTZs2sX79egICApg5cybjxo3jb3/7GwBVVVWMGTOGiIgIdu3aRXZ2Ng8//DAeHh4sXbrUCacjIiIi7YHDAcXd3Z2IiIgrthcWFrJ69WrWrl3LiBEjAFizZg19+/Zl9+7dDB06lM8++4yjR4+yfft2wsPDGTBgAM8//zy//e1vWbRoEZ6entd/RiIiItLmOTwG5bvvviMyMpKYmBgmTpzImTNnAMjIyMBisTBy5Eh72T59+tCtWzfS09MBSE9Pp3///oSHh9vLJCQkUFRUxJEjRxpss6KigqKiojovERERab8cCihDhgzhnXfeYcuWLaxatYpTp05xxx13UFxcjNlsxtPTk8DAwDrHhIeHYzabATCbzXXCSe3+2n0NSU1NJSAgwP6KiopypNsiIiLSxjj0Fc8999xj//vNN9/MkCFD6N69Ox988AE+Pj5O71yt+fPnM2fOHPv7oqIihRQREZF27LoeMw4MDCQ2NpaTJ08SERFBZWUlBQUFdcrk5OTYx6xERERc8VRP7fv6xrXU8vLywt/fv85LRERE2q/rCiglJSV8//33mEwmBg4ciIeHBzt27LDvP378OGfOnCE+Ph6A+Ph4Dh06RG5urr3Mtm3b8Pf3Jy4u7nq6IiIiIu2IQ1/x/Od//if33Xcf3bt3Jysri2effRY3Nzd+9atfERAQwJQpU5gzZw7BwcH4+/sza9Ys4uPjGTp0KACjRo0iLi6Ohx56iOXLl2M2m1mwYAFJSUl4eXk1ywmKiIhI2+NQQPnhhx/41a9+xcWLFwkNDeX2229n9+7dhIaGAvDyyy/j6upKYmIiFRUVJCQk8MYbb9iPd3NzY+PGjUyfPp34+Hh8fX2ZNGkSixcvdu5ZiYi0Q9kl2eRX5FNcYAEgsyCT874eLdJ2kFcQJj9Ti7QlAg4GlPfff/+q+729vUlLSyMtLa3BMt27d2fz5s2ONCsi0uFll2Qz9pOxlFnL6FJyA/9BMvO+mscFvx9apH0fdx8+GfuJQoq0GIcnahMRkZaXX5FPmbWM1DtSCS2JYt+hiyy7Yxmduzb/HZTMwkzmfzWf/Ip8BRRpMQooIiJtSExADKHuUezjIjGBMYSGdG7tLok0C61mLCIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGo4AiIiIihqOAIiIiIoajgCIiIiKGc10BZdmyZbi4uDB79mz7tvLycpKSkggJCcHPz4/ExERycnLqHHfmzBnGjBlDp06dCAsLIzk5GavVej1dERERkXakyQHlm2++4b/+67+4+eab62x/8skn+etf/8r69ev58ssvycrKYty4cfb9VVVVjBkzhsrKSnbt2sUf//hH3nnnHZ555pmmn4WIiIi0K00KKCUlJUycOJG33nqLoKAg+/bCwkJWr17NSy+9xIgRIxg4cCBr1qxh165d7N69G4DPPvuMo0eP8u677zJgwADuuecenn/+edLS0qisrHTOWYmIiEib1qSAkpSUxJgxYxg5cmSd7RkZGVgsljrb+/TpQ7du3UhPTwcgPT2d/v37Ex4ebi+TkJBAUVERR44cqbe9iooKioqK6rxERESk/XJ39ID333+f/fv3880331yxz2w24+npSWBgYJ3t4eHhmM1me5kfh5Pa/bX76pOamspzzz3naFdFRAzNkpWFNT+/cYULTxFttsHxTMorau42l3//PWXFHk1q2z0oCI/IyCYdK9ISHAooZ8+e5Te/+Q3btm3D29u7ufp0hfnz5zNnzhz7+6KiIqKiolqsfRERZ7NkZfH9mHuxlZU1qrwL8ALAmmSy/aJg0Dyyk+dSUnK2Se27+PjQc9NGhRQxLIcCSkZGBrm5ufzbv/2bfVtVVRU7d+5k5cqVbN26lcrKSgoKCurcRcnJySEiIgKAiIgI9u7dW6fe2qd8astczsvLCy8vL0e6KiJiaNb8fGxlZUSuWI5nTMw1y58qPMW8r+ax7I5lmCpugHV5mFYsp0uY43dQKjMzyUqeizU/XwFFDMuhgHL33Xdz6NChOtsmT55Mnz59+O1vf0tUVBQeHh7s2LGDxMREAI4fP86ZM2eIj48HID4+npSUFHJzcwkLCwNg27Zt+Pv7ExcX54xzEhFpMzxjYvDp1+/aBS+6cOo7F7gxBu/SKCAP75498enWudn7KNIaHAoonTt35qabbqqzzdfXl5CQEPv2KVOmMGfOHIKDg/H392fWrFnEx8czdOhQAEaNGkVcXBwPPfQQy5cvx2w2s2DBApKSknSXRERERIAmDJK9lpdffhlXV1cSExOpqKggISGBN954w77fzc2NjRs3Mn36dOLj4/H19WXSpEksXrzY2V0RERGRNuq6A8oXX3xR5723tzdpaWmkpaU1eEz37t3ZvHnz9TYtIiIi7ZTW4hERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw1FAEREREcNRQBERERHDUUARERERw3Fv7Q6IiEjrK84rp7zEUv++AgtdSm6g+JyF86XFjarP28+DzsHezuyidDAKKCIiHVxxXjlrF+3GWlndYJn/IJl9hy6yj4uNqtPd05UJi4YqpEiTKaCIiHRw5SUWrJXVjJwcR7DJ94r9mQWZzPtqHsvuWEZMYMw168vLLmX7mqOUl1gUUKTJFFBERASAYJMvod06X7H9vK8HF/x+oHNXD0JDrtzf3LJLssmvyL++SgpP4QKcKjwFF10afViQVxAmP9P1tS1NooAiIiKGlV2SzdhPxlJmLbuueqLNNl4A5n01j1PfNT6g+Lj78MnYTxRSWoECioiIGFZ+RT5l1jJS70glJuDaXy816HgmrElm2R3L4MbG1ZNZmMn8r+aTX5GvgNIKFFBEpNmdKygjv7SyxdsN8vWka6BPi7crzhcTEENcSFyTjy8LsHEaiA6Ixuc66pGWo4AiIs3qXEEZI1/8kjJLVYu37ePhxvan7lRIkTbLKeNvGlJ0Gjw9av708rxid2uPv1FAEZFmlV9aSZmlilceHECvML8Wa/dkbgmz1x0kv7RSAUXaJGeNv7mqribYs7DeXa09/kYBRURaRK8wP27qGtDa3RBpM5w2/qYh50/Ahqkw7m0Ija2zywjjbxRQREREDOx6x980qKISKi3g3wMMOC5Ha/GIiIiI4SigiIiIiOEooIiIiIjhOBRQVq1axc0334y/vz/+/v7Ex8fz6aef2veXl5eTlJRESEgIfn5+JCYmkpOTU6eOM2fOMGbMGDp16kRYWBjJyclYrVbnnI2IiIi0Cw4FlBtuuIFly5aRkZHBvn37GDFiBGPHjuXIkSMAPPnkk/z1r39l/fr1fPnll2RlZTFu3Dj78VVVVYwZM4bKykp27drFH//4R9555x2eeeYZ556ViIiItGkOPcVz33331XmfkpLCqlWr2L17NzfccAOrV69m7dq1jBgxAoA1a9bQt29fdu/ezdChQ/nss884evQo27dvJzw8nAEDBvD888/z29/+lkWLFuHpeeVEMSIiItLxNHkMSlVVFe+//z6lpaXEx8eTkZGBxWJh5MiR9jJ9+vShW7dupKenA5Cenk7//v0JDw+3l0lISKCoqMh+F6Y+FRUVFBUV1XmJiIhI++XwPCiHDh0iPj6e8vJy/Pz8+Oijj4iLi+PgwYN4enoSGBhYp3x4eDhmsxkAs9lcJ5zU7q/d15DU1FSee+45R7sqIiJOlFmY2ahyxQWWmvIFmZz39fjXjsJTuACnCk/BxcatKNzYNqX9cTig3HjjjRw8eJDCwkL+8pe/MGnSJL788svm6Jvd/PnzmTNnjv19UVERUVFRzdqmiIjUCPIKwsfdh/lfzW9U+S4lN/AfJDPvq3lc8PvBvj3abOMFYN5X8zj1XeMCCtRMuR7kFeRot6WNczigeHp60qtXLwAGDhzIN998w6uvvsqDDz5IZWUlBQUFde6i5OTkEBERAUBERAR79+6tU1/tUz61Zerj5eWFl5eXo10VEREnMPmZ+GTsJ41etK74nIV9hy6y7I5ldO76ozsoxzNhTTLL7lgGNzZ+6vbWXrROWsd1T3VfXV1NRUUFAwcOxMPDgx07dpCYmAjA8ePHOXPmDPHx8QDEx8eTkpJCbm4uYWFhAGzbtg1/f3/i4ow3za6IiNQw+ZkaHRLOlxazj4vEBMYQGtLZvr0swMZpIDogGh8DTq0uxuJQQJk/fz733HMP3bp1o7i4mLVr1/LFF1+wdetWAgICmDJlCnPmzCE4OBh/f39mzZpFfHw8Q4cOBWDUqFHExcXx0EMPsXz5csxmMwsWLCApKUl3SERERMTOoYCSm5vLww8/THZ2NgEBAdx8881s3bqVn/70pwC8/PLLuLq6kpiYSEVFBQkJCbzxxhv2493c3Ni4cSPTp08nPj4eX19fJk2axOLFi517ViIiItKmORRQVq9efdX93t7epKWlkZaW1mCZ7t27s3nzZkeaFRERkQ5Ga/GIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhOLRYoIhIR5ddkk1+Rb5DxxQXWADILMjkvK9HzcbCU7gApwpPwUWXa9aRWZjpaFdF2jQFFBGRRsouyWbsJ2Mps5Y5dFyXkhv4D5KZ99U8Lvj9AEC02cYLwLyv5nHqu2sHFAAfdx+CvIKg1NGei7Q9CigiIo2UX5FPmbWM1DtSiQmIafRxxecs7Dt0kWV3LKNz13/eQTmeCWuSWXbHMrixcXUFeQVh8jNxPq+4Kd0XaVMUUEREHBQTEENcSFyjy58vLWYfF4kJjCE0pDMAZQE2TgPRAdH4OFCXSEehgCIici0FZ+HSRSg6XfP+/AmoqGz88eet//zzOLj/89fu+VP/qivLUv9xnUIgMKpJXRZp6xRQRESupuAspA0GyyXw9ICuJtgwFSobCBX1scQAL8KGx8Djn4Nd8zyA0JptwQ3U5dEJkvYqpEiHpIAiInI1ly7WhJNxb4GnJ+xZCOPeBv8eja8j2wpvFdXUYfrnr90Tp+Cz39Vsi42+8pgLJ2rCy6WLCijSISmgiIg0RpdY8PKs+XtoLDgybsRaDHwDoTdCZM0YFPI9/lVXZD+ndlWkPdBEbSIiImI4CigiIiJiOAooIiIiYjgKKCIiImI4CigiIiJiOAooIiIiYjh6zFhEROQqmnUl6aLTNRMAFp3+12PsLdFuG6CAIiIiUo8gryB83H2Y/9X85m2oq6lmAsB62Few7oAUUEREROph8jPxydhPyK/Ib75Gzp+oWTph3Ns1k/ZdpnYF645IAUVERKQBJj9T8waEisqadZ38ezg2O3EHoEGyIiIiYjgKKCIiImI4CigiIiJiOAooIiIiYjgOBZTU1FRuvfVWOnfuTFhYGD//+c85fvx4nTLl5eUkJSUREhKCn58fiYmJ5OTk1Clz5swZxowZQ6dOnQgLCyM5ORmr1Xr9ZyMiIiLtgkNP8Xz55ZckJSVx6623YrVa+d3vfseoUaM4evQovr6+ADz55JNs2rSJ9evXExAQwMyZMxk3bhx/+9vfAKiqqmLMmDFERESwa9cusrOzefjhh/Hw8GDp0qXOP0ORepwrKCO/tLJV2g7y9aRroE+rtC0i0lY4FFC2bNlS5/0777xDWFgYGRkZ/Pu//zuFhYWsXr2atWvXMmLECADWrFlD37592b17N0OHDuWzzz7j6NGjbN++nfDwcAYMGMDzzz/Pb3/7WxYtWoSnp2d9TYs4zbmCMka++CVllqpWad/Hw43tT92pkCIichXXNQ9KYWEhAMHBwQBkZGRgsVgYOXKkvUyfPn3o1q0b6enpDB06lPT0dPr37094eLi9TEJCAtOnT+fIkSP85Cc/uZ4uiVxTfmklZZYqXnlwAL3C/Fq07ZO5Jcxed5D80koFFLluedmlTTquPNdCsV8UF3IteHcubnI9Is2pyQGlurqa2bNnM2zYMG666SYAzGYznp6eBAYG1ikbHh6O2Wy2l/lxOKndX7uvPhUVFVRUVNjfFxUVNbXbIna9wvy4qWtAa3dDxGHefh64e7qyfc3RplcyaB6sywPyAHD3dMXbz8M5HRRxgiYHlKSkJA4fPszXX3/tzP7UKzU1leeee67Z2xERaQs6B3szYdFQykssTTq+/PvvyU6ei2nFcrx79gRqQk/nYG9ndlPkujQpoMycOZONGzeyc+dObrjhBvv2iIgIKisrKSgoqHMXJScnh4iICHuZvXv31qmv9imf2jKXmz9/PnPmzLG/LyoqIioqqildFxFpFzoHezc5UJQVe1BScpYuYR74dOvs5J6JOIdDjxnbbDZmzpzJRx99xOeff050dHSd/QMHDsTDw4MdO3bYtx0/fpwzZ84QHx8PQHx8PIcOHSI3N9deZtu2bfj7+xMXV/86BF5eXvj7+9d5iYiISPvl0B2UpKQk1q5dyyeffELnzp3tY0YCAgLw8fEhICCAKVOmMGfOHIKDg/H392fWrFnEx8czdOhQAEaNGkVcXBwPPfQQy5cvx2w2s2DBApKSkvDy8nL+GYqIiEib41BAWbVqFQB33XVXne1r1qzhkUceAeDll1/G1dWVxMREKioqSEhI4I033rCXdXNzY+PGjUyfPp34+Hh8fX2ZNGkSixcvvr4zERERkXbDoYBis9muWcbb25u0tDTS0tIaLNO9e3c2b97sSNMiIuJklZmZzVJveW7N4N3y77+nrPhfTwY1V3vSPl3XPCgiItL2uAcF4eLjQ1by3Gapv9gvCgbNIzt5LiUlZ+vsc/HxwT0oqFnalfZFAUWkg2it6f1P5pa0eJtydR6RkfTctBFrfn6z1H8h1wLr8jCtWE6XsLpzq7gHBeERGdks7Ur7ooAi0gEYYXr/IF8tY2EkHpGRzRYUvDsXA3l49+ypx5ilyRRQRDqA1pzeH7RAoog4TgFFpAPR9P4i0lY4NFGbiIiISEtQQBERERHDUUARERERw1FAEREREcPRIFkR6fAsWVkNzwly/hTkecCJU+DpQbTZBsczKQu49szateqbWVWzqopcnQKKiHRolqwsvh9zL7aysquUCoXPfocL8ALAmmROO9BGQzOralZVkYYpoIhIHVe9m9CMWmuGUWt+PrayMiJXLMczJubKAudPwIbHYNxbnPL0YN5X81h2xzKiA6Ib3UZDM6tqVlWRhimgiIhd4+4mNA8XHx96btrYah/YnjEx+PTrd+WOLAsEWyA2Grw8OfWdC9wYg09IXKPr1syqbUTBWbh0sWXbvHCiZdtrQxRQRMTumncTmkllZiZZyXOx5ufrjsLlWusDrFMIBEa1TtutoeAspA0Gy6WWb9ujU831ljoUUETkCg3eTZCW0ymk5oNrw2Ot075HJ0ja23FCyqWLNeFk3FvQJbZl2+5oYbCRFFBERIwoMKomILT0Vw5Qc9dmw2M1bXe0D84usRA5oLV7ISigiLSKk7kl7bo9cZLAqI4XEET+SQFFpAUF+Xri4+HG7HUHW7xtHw83gnw9W7xdEZGmUEARaUFdA33Y/tSd5JdWtnjbQb6edA30afF2RUSaQgFFpIV1DfRRUBARuQatxSMiIiKGo4AiIiIihqOAIiIiIoajMSgi0uZkl2STX3H19YJOFZXg6n2OU0XHcfX2a7hg4SlcgFOFp+Ciy5X7i06DpwcUnSbTs3G/Ms8VlNUZCF2cWzM76cncEnLcqhtVR1NpMLS0FwooIgbUWgv2VWZmtnibjsouyWbsJ2Mps157vSDfaPjd3quXiTbbeAGY99W8mnV26tPVBHsWAuDj7kOQV8MrEJ8rKGPki19SZqmybwuzujAJb37z/gFy3W3X7Pf18PFwY/tTdyqkSJungCJiMK25YB/ULNrnHtTwB3Bry6/Ip8xaRuodqcQENLxe0Pe5Jfxm3UFefXAAPcOucgfleCasSWbZHcvgxoZWM54K496G0FiCvIIw+Zka7l9pJWWWKl55cAC9/tlucfYl9r99jFfH/4TOpk6NPldHncwtYfa6g+SXViqgSJungCJiMK21YF8t96CgNrFgX0xADHFXWVG4uryQ6vLzRPvfSFxIQIPlygJsnAaiA6LrX6G4ohIqLeDfAxxYwbhXmB83da1p93yVK/v/uS20q1YzFmkMBRQRg9KCfSLSkSmgiIhhNGoMTOEpos02OJ5JWcBVxnPkltCz4Ac48S1lBQ1/xdMWxt2IdEQKKCLS6tyDgnDx8SEree41y7oALwCsSeb0Vcq5ASsBvuCq5cD4425EOiIFFGlVlz+O2RK0sq/xeERG0nPTxqs/uVScA+WFnCrNYt7hVSy7aTrRvg2Plfkh/xIrPjtB8qhYbgi6+sBU94DOeJALWblX7rxworGnIc5QcBYuXXR+vedP/fPPE5BluXK//p0NRwFFWk19j2O2FK3sazwekZEND84tOAtpI8FyCTw9ONXVBH9/Fp/Kej5o/qk38Idw4O/O6Fwn6BTihIrkqgrOQtrgmn9nZ8vzAEJhw2MQ3MDPjf6dDUUBRVpNfY9jthRNZtXGXLpY86E17i3w9KyZk2Tc2zVP1jTg5PkSfvP+QV4dP4Beodf589UpBAKjrq8OubYf/zt3iXVu3SdOwWe/q6k7Nrr+Mvp3NhQFFGl1P34cU+SqusSC1z/vfIXGXvWx33JbIUdshZR36Q+R+vlqU7rEQuQA59aZ71HzZ2gsROrpuLZAa/GIiIiI4Th8B2Xnzp2sWLGCjIwMsrOz+eijj/j5z39u32+z2Xj22Wd56623KCgoYNiwYaxatYrevXvby+Tl5TFr1iz++te/4urqSmJiIq+++ip+fi17m19E2r+WHhStQdgizuFwQCktLeWWW27h0UcfZdy4cVfsX758Oa+99hp//OMfiY6OZuHChSQkJHD06FG8vb0BmDhxItnZ2Wzbtg2LxcLkyZOZNm0aa9euvf4zEmlBxXnllJc0PFDTUd5+Hvre1UmCfD3x8XBj9rqDLd62BmGLXD+Hfxfec8893HPPPfXus9lsvPLKKyxYsICxY8cC8Kc//Ynw8HA+/vhjxo8fz7Fjx9iyZQvffPMNgwYNAuD1119n9OjR/P73vyeyDUyxLQI14WTtot1YK523Oq27pyvjJgQ7rb6OrGugD9ufurPFH2MHDcIWcQan/s/aqVOnMJvNjBw50r4tICCAIUOGkJ6ezvjx40lPTycwMNAeTgBGjhyJq6sre/bs4Re/+MUV9VZUVFBRUWF/X1RU5MxuizRJeYkFa2U1IyfHEWzyve768rJL2b7mKOVlzgs8HV3XQB8FBZE2yqkBxWw2AxAeHl5ne3h4uH2f2WwmLCysbifc3QkODraXuVxqairPPfecM7sq0iiWrKwGJw8rz635aqfTJTN+xR7X3Vb5pZr6LOfOXXddIiJtXZv4unv+/PnMmTPH/r6oqIioKD2rLs3LkpXF92PuxVZWVu/+Yr8oGDSP7OS5lJScve72auu78Mqr+GvqdRHp4JwaUCIiIgDIycnBZDLZt+fk5DBgwAB7mdzcutNJW61W8vLy7MdfzsvLCy8vL2d2VX6kNaabB+M/7WDNz8dWVkbkiuV4xsRcsf9CrgXW5WFasZwuYdd/B+XH9UXcGNbwrKoiIh2AUwNKdHQ0ERER7Nixwx5IioqK2LNnD9OnTwcgPj6egoICMjIyGDhwIACff/451dXVDBkyxJndkUZozenmoW087eAZE4NPvysndvLuXAzk4d2zJz7dOl93Oz+uzyPy+utrbtkl2eRXXGXtHGcqOg2eHlB0mkzPNnHjV0Suk8P/pZeUlHDy5En7+1OnTnHw4EGCg4Pp1q0bs2fPZsmSJfTu3dv+mHFkZKR9rpS+ffvys5/9jMcee4w333wTi8XCzJkzGT9+vJ7gaQWtOd086GmHtiq7JJuxn4ylzFr/11/NoqupZop7wMfdhyAvfQUm0p45HFD27dvH8OHD7e9rx4ZMmjSJd955h7lz51JaWsq0adMoKCjg9ttvZ8uWLfY5UADee+89Zs6cyd13322fqO21115zwulIU2m6eXFEfkU+ZdYyUu9IJSbgyq+/nO78CdgwtWb9ndBYgryCMPmZrn2ciLRZDgeUu+66C5vN1uB+FxcXFi9ezOLFixssExwcrEnZRNqBmIAY4q6yHo7TVFRCpaVmccCWaE9EWp2+zBURkfpdONG0485b//nncXB34GOmqe1Ju6SAIiIidXUKAY9OsOGxph1viQFerDneI9OxYz061bQvHZ4CioiI1BUYBUl74dLFph2fbYW3imDcW2By8GOmU0hN+9LhKaCIiMiVAqOaHhSsxcA3EHojtIFH5sWYXFu7AyIiIiKXU0ARERERw1FAEREREcNRQBERERHDUUARERERw9FTPCIi9SjOK6e8xOKUuvKyS51Sj0hHooAiInKZ4rxy1i7ajbWy2ml1unu64u3n4bT6RNo7BRQRkcuUl1iwVlYzcnIcwSZfp9Tp7edB52DvaxcUEUABRUSkQcEmX0K7aaIxkdagQbIiIiJiOAooIiIiYjgKKCIiImI4GoMiYjBGfSRVgzxFpCUpoIgYhLefB+6ermxfc7S1u1Ivd09XJiwaqpAiIi1CAUXEIDoHezNh0VCnTQ7mTHnZpWxfc5TyEosCioi0CAUUEQPpHOytACAiggbJioiIiAHpDopIG5Zdkk1+RX6zt1NcUPO1U2ZBJud9PcgszGz2NkWkY1NAEWmjskuyGfvJWMqsZc3eVpeSG/gPkpn31Twu+P0AgI+7D0FeQc3etoh0TAooBnKuoIz80soWbfNkbkmLttcUlqwsrPnNf5fgcpWZxr5LkF+RT5m1jNQ7UokJiGnWtorPWdh36CLL7lhG5641C94FeQVh8jM1a7si0nEpoBjEuYIyRr74JWWWqhZv28fDjSBfzxZvtzEsWVl8P+ZebGXNf5egPi4+PrgHGfsuQUxADHEhcc3axvnSYvZxkZjAGEJDtDaNiDQ/BRSDyC+tpMxSxSsPDqBXmF+Lth3k60nXQJ8WbbOxrPn52MrKiFyxHM+Y5r1LUB/3oCA8IiNbvF0RkY5OAcVgeoX5cVPXgNbuhuF4xsTg069fa3dDRERaiB4zFhEREcPRHRQRaTRnrhOktX1E5GoUUETkmppjnSBnr+1TnFfutGUCjLpgo0hHooAiItfk7HWCatf2yfqugGCT77UPOG8FSwxkW8FafMXusuJKPv2vQ1grq53SP6gJUN5+Hk6rT0Qco4AiIo3izHWCmnZH5kV4qwj4pt697p6u3DfrFnw6O+eReX0FJdK6FFBEpMU5fEfm/HHY8BiMewtCb6y3iAKFSPuigCIircKhOzLu7uCRCSZ3iNREcSIdQasGlLS0NFasWIHZbOaWW27h9ddfZ/Dgwa3ZJRG5loKzcOliy7Z54UTLticira7VAsq6deuYM2cOb775JkOGDOGVV14hISGB48ePExYW1lrdEpGrKTgLaYPBcqnl2/boBJ1CWr5dEWkVrRZQXnrpJR577DEmT54MwJtvvsmmTZv4v//3/zJv3rzW6hagRfsa0hqL9hl6wb5iMwDnf9jD+Ust/++XWXqu5i/nT0BFC/28XjhRE07GvQVdYlumzVqdQiAwqmXbFJFW0yoBpbKykoyMDObPn2/f5urqysiRI0lPT7+ifEVFBRUVFfb3hYWFABQVFTm9b1kFZdy/8mvKLc57XLGxvD1cca8qp6jIpcXbvhZLdjanHvhlqyza5+LjwyV3dyzN8O/dZAU/UPz/JlFW+QxP/O0Vsjpnt0o3fKqrcf9/kymqbsFFJt19IPAm8Luh5dqsZaSfAQMqKS6iuuISJcVFrfp7pLi4mLLKUoqLi/AqsrVaP36srKSEkqoqikpKjPW7pDUVl0CFrebPy65JSXEJVWVVlBSXUOThvOtV+7ltszXi58LWCs6dO2cDbLt27aqzPTk52TZ48OAryj/77LM2QC+99NJLL730agevs2fPXjMrtImneObPn8+cOXPs76urq8nLyyMkJAQXF+PdbWisoqIioqKiOHv2LP7+/q3dnVaj66BrUEvXoYauQw1dhxrt6TrYbDaKi4uJbMQq8a0SULp06YKbmxs5OTl1tufk5BAREXFFeS8vL7y8vOpsCwwMbM4utih/f/82/0PnDLoOuga1dB1q6DrU0HWo0V6uQ0BAQKPKtcpqxp6engwcOJAdO3bYt1VXV7Njxw7i4+Nbo0siIiJiIK32Fc+cOXOYNGkSgwYNYvDgwbzyyiuUlpban+oRERGRjqvVAsqDDz7I+fPneeaZZzCbzQwYMIAtW7YQHh7eWl1qcV5eXjz77LNXfH3V0eg66BrU0nWooetQQ9ehRke9Di42W2Oe9RERERFpOa0yBkVERETkahRQRERExHAUUERERMRwFFBERETEcBRQmllaWho9evTA29ubIUOGsHfv3quWLygoICkpCZPJhJeXF7GxsWzevLmFett8HLkOd911Fy4uLle8xowZ04I9dj5HfxZeeeUVbrzxRnx8fIiKiuLJJ5+kvLy8hXrbfBy5DhaLhcWLF9OzZ0+8vb255ZZb2LJlSwv2tnns3LmT++67j8jISFxcXPj444+vecwXX3zBv/3bv+Hl5UWvXr145513mr2fzcnRa5Cdnc2ECROIjY3F1dWV2bNnt0g/m5uj12HDhg389Kc/JTQ0FH9/f+Lj49m6dWvLdLaFKaA0o3Xr1jFnzhyeffZZ9u/fzy233EJCQgK5ubn1lq+srOSnP/0pp0+f5i9/+QvHjx/nrbfeomvXri3cc+dy9Dps2LCB7Oxs++vw4cO4ubnxwAMPtHDPncfRa7B27VrmzZvHs88+y7Fjx1i9ejXr1q3jd7/7XQv33LkcvQ4LFizgv/7rv3j99dc5evQojz/+OL/4xS84cOBAC/fcuUpLS7nllltIS0trVPlTp04xZswYhg8fzsGDB5k9ezZTp05t0x9Mjl6DiooKQkNDWbBgAbfccksz967lOHoddu7cyU9/+lM2b95MRkYGw4cP57777mvz/03UyznL/0l9Bg8ebEtKSrK/r6qqskVGRtpSU1PrLb9q1SpbTEyMrbKysqW62CIcvQ6Xe/nll22dO3e2lZSUNFcXm52j1yApKck2YsSIOtvmzJljGzZsWLP2s7k5eh1MJpNt5cqVdbaNGzfONnHixGbtZ0sCbB999NFVy8ydO9fWr1+/OtsefPBBW0JCQjP2rOU05hr82J133mn7zW9+02z9aS2OXodacXFxtueee875HWpluoPSTCorK8nIyGDkyJH2ba6urowcOZL09PR6j/nv//5v4uPjSUpKIjw8nJtuuomlS5dSVVXVUt12uqZch8utXr2a8ePH4+vr21zdbFZNuQa33XYbGRkZ9q8/MjMz2bx5M6NHj26RPjeHplyHiooKvL2962zz8fHh66+/bta+Gk16enqd6waQkJDQ6P+GpP2qrq6muLiY4ODg1u6K07WJ1YzbogsXLlBVVXXFzLjh4eF8++239R6TmZnJ559/zsSJE9m8eTMnT55kxowZWCwWnn322ZbottM15Tr82N69ezl8+DCrV69uri42u6ZcgwkTJnDhwgVuv/12bDYbVquVxx9/vE1/xdOU65CQkMBLL73Ev//7v9OzZ0927NjBhg0b2nRobwqz2VzvdSsqKqKsrAwfH59W6pm0tt///veUlJTwy1/+srW74nS6g2Ig1dXVhIWF8Yc//IGBAwfy4IMP8vTTT/Pmm2+2dtdazerVq+nfvz+DBw9u7a60qC+++IKlS5fyxhtvsH//fjZs2MCmTZt4/vnnW7trLerVV1+ld+/e9OnTB09PT2bOnMnkyZNxddWvLpG1a9fy3HPP8cEHHxAWFtba3XE63UFpJl26dMHNzY2cnJw623NycoiIiKj3GJPJhIeHB25ubvZtffv2xWw2U1lZiaenZ7P2uTk05TrUKi0t5f3332fx4sXN2cVm15RrsHDhQh566CGmTp0KQP/+/SktLWXatGk8/fTTbfIDuinXITQ0lI8//pjy8nIuXrxIZGQk8+bNIyYmpiW6bBgRERH1Xjd/f3/dPemg3n//faZOncr69euv+PqvvWh7v+XaCE9PTwYOHMiOHTvs26qrq9mxYwfx8fH1HjNs2DBOnjxJdXW1fduJEycwmUxtMpxA065DrfXr11NRUcGvf/3r5u5ms2rKNbh06dIVIaQ2uNra6PJZ1/Oz4O3tTdeuXbFarXz44YeMHTu2ubtrKPHx8XWuG8C2bduued2kffrzn//M5MmT+fOf/9zmp1+4qtYepduevf/++zYvLy/bO++8Yzt69Kht2rRptsDAQJvZbLbZbDbbQw89ZJs3b569/JkzZ2ydO3e2zZw503b8+HHbxo0bbWFhYbYlS5a01ik4haPXodbtt99ue/DBB1u6u83C0Wvw7LPP2jp37mz785//bMvMzLR99tlntp49e9p++ctfttYpOIWj12H37t22Dz/80Pb999/bdu7caRsxYoQtOjralp+f30pn4BzFxcW2AwcO2A4cOGADbC+99JLtwIEDtn/84x82m81mmzdvnu2hhx6yl8/MzLR16tTJlpycbDt27JgtLS3N5ubmZtuyZUtrncJ1c/Qa2Gw2e/mBAwfaJkyYYDtw4IDtyJEjrdF9p3H0Orz33ns2d3d3W1pami07O9v+KigoaK1TaDYKKM3s9ddft3Xr1s3m6elpGzx4sG337t32fXfeeadt0qRJdcrv2rXLNmTIEJuXl5ctJibGlpKSYrNarS3ca+dz9Dp8++23NsD22WeftXBPm48j18BisdgWLVpk69mzp83b29sWFRVlmzFjRpv/YLbZHLsOX3zxha1v3742Ly8vW0hIiO2hhx6ynTt3rhV67Vz/8z//YwOueNWe+6RJk2x33nnnFccMGDDA5unpaYuJibGtWbOmxfvtTE25BvWV7969e4v33ZkcvQ533nnnVcu3Jy42Wxu9XywiIiLtlsagiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4SigiIiIiOEooIiIiIjhKKCIiIiI4fx/bQUnqPZO6r8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if we are not allowed to use multiple CCB's in a single HD 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCBno 0 with pop 13737.0 would be used 1.2015939683574768 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 1 with pop 169151.0 would be used 2.2715834045673704 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 2 with pop 171003.0 would be used 1.7638767243359472 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 3 with pop 92501.0 would be used 2.0492571921493203 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 4 with pop 51938.0 would be used 1.576935985060704 if we added it to all adjoining districts with no 2-CCB districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\")\n",
    "CCBwouldUse = [0. for i in range(nCCBs)]\n",
    "CCBaddCandidates = [list() for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    ccbNbrSet = set(unitNbrs[jNo])\n",
    "    withCCBpopRat = list()\n",
    "    for t in range(nHDs):\n",
    "        if len(ccbNbrSet.intersection(set(HDunitList[t]))) > 0:\n",
    "            CCBwouldUse[j] += HDweight[t] * nDistricts\n",
    "            CCBaddCandidates[j].append(t)\n",
    "            withCCBpopRat.append((np.sum([unitPop[u] for u in HDunitList[t]]) + CCBpop[j]) / aDP )\n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",r3(CCBwouldUse[j]),\"if we added it to all adjoining districts\")\n",
    "    print(\"Here is the histogram of relative district pop with these added\")\n",
    "    plt.hist(withCCBpopRat,histtype=\"step\",label=\"CCB \"+str(j))\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "avoidMultiCCBuse = int(input(\"enter 1 if we are not allowed to use multiple CCB's in a single HD\"))  #option by state\n",
    "if avoidMultiCCBuse == 1:\n",
    "    for j in range(nCCBs):  #this block -- preventing HDs from picking up multiple CCB's; instead, pick up the closest one  \n",
    "        jNo = allUnits.index(j+0.25)\n",
    "        for jj in range(j+1, nCCBs):\n",
    "            jjNo = allUnits.index(j+0.25)\n",
    "            for t in CCBaddCandidates[j].copy():\n",
    "                if t in CCBaddCandidates[j]:\n",
    "                    if t in CCBaddCandidates[jj].copy():\n",
    "                        dist_j, dist_jj = hdCP[t].distance(unitCP[jNo]), hdCP[t].distance(unitCP[jjNo])\n",
    "                        if dist_j > dist_jj:\n",
    "                            CCBaddCandidates[j].remove(t)  #for MN, don't allow any districts with two CCB's\n",
    "                            CCBwouldUse[j] -= HDweight[t] * nDistricts\n",
    "                        else:\n",
    "                            CCBaddCandidates[jj].remove(t)\n",
    "                            CCBwouldUse[jj] -= HDweight[t] * nDistricts\n",
    "for j in range(nCCBs):    \n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\"if we added it to all adjoining districts with no 2-CCB districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "0d38eb0e-b516-4fd4-bb9e-6ca0eecfa772",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\n",
      "For PA, I recommend CCBuse of 1.03, 1.03, 1.01 to account for later shedding\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 0 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 0 is 1.02165 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 1 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 1 is 1.02047 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 2 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 2 is 1.02003 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 3 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 3 is 1.02023 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter target CCBuse for CCB 4 I reco 1.02, as we may lose a little later 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 4 is 1.02693 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": 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EFAAAYB0CCgAAsE5UAWXRokW69NJL5Xa75Xa75ff7tWbNGmf82LFjKioqUu/evdWjRw8VFBSopqYmYh/V1dXKz89XcnKy0tLSNGPGDDU1NbXP0QAAgC4hqoBy3nnnac6cOaqsrNSWLVt0ww03aMyYMdqxY4ckafr06Xr55Ze1YsUKrV+/XgcOHNDYsWOd7Y8fP678/Hw1NDRo48aNWrZsmZYuXapZs2a171EBAIBOLcYYY9qyg9TUVP3+97/Xrbfeqr59+2r58uW69dZbJUm7d+/W4MGDFQgENGLECK1Zs0Y/+clPdODAAXm9XknS4sWLdf/99+vTTz9VYmLit3rPcDgsj8ejUCgkt9vdlukDXV7/B17p6ClE7eM5+R09BQBnQTS/v8/4GpTjx4/r+eef19GjR+X3+1VZWanGxkbl5OQ4NYMGDVJmZqYCgYAkKRAIaOjQoU44kaTc3FyFw2HnLExr6uvrFQ6HIxYAANB1RR1Qtm3bph49esjlcunuu+/WypUrlZWVpWAwqMTERKWkpETUe71eBYNBSVIwGIwIJy3jLWOnUlpaKo/H4ywZGRnRThsAAHQiUQeUiy++WFu3blVFRYWmTJmiCRMmaOfOnWdjbo6SkhKFQiFn2b9//1l9PwAA0LHio90gMTFRF110kSRp2LBh2rx5s/7zP/9Tt99+uxoaGlRXVxdxFqWmpkY+n0+S5PP59M4770Tsr+Uun5aa1rhcLrlcrminCgAAOqk2PwelublZ9fX1GjZsmBISElReXu6MVVVVqbq6Wn6/X5Lk9/u1bds21dbWOjVlZWVyu93Kyspq61QAAEAXEdUZlJKSEuXl5SkzM1OHDx/W8uXL9de//lWvvfaaPB6PJk6cqOLiYqWmpsrtdmvatGny+/0aMWKEJGn06NHKysrS+PHjNXfuXAWDQc2cOVNFRUWcIQEAAI6oAkptba1+9rOf6eDBg/J4PLr00kv12muv6cc//rEkad68eYqNjVVBQYHq6+uVm5urhQsXOtvHxcVp9erVmjJlivx+v7p3764JEyZo9uzZ7XtUAACgU2vzc1A6As9BAb49noMCwBbn5DkoAAAAZwsBBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWIaAAAADrEFAAAIB1CCgAAMA6BBQAAGAdAgoAALAOAQUAAFiHgAIAAKxDQAEAANYhoAAAAOsQUAAAgHUIKAAAwDoEFAAAYB0CCgAAsA4BBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWIaAAAADrEFAAAIB1CCgAAMA6BBQAAGAdAgoAALAOAQUAAFiHgAIAAKxDQAEAANYhoAAAAOsQUAAAgHUIKAAAwDoEFAAAYB0CCgAAsA4BBQAAWCeqgFJaWqof/OAH6tmzp9LS0nTLLbeoqqoqoubYsWMqKipS79691aNHDxUUFKimpiaiprq6Wvn5+UpOTlZaWppmzJihpqamth8NAADoEqIKKOvXr1dRUZE2bdqksrIyNTY2avTo0Tp69KhTM336dL388stasWKF1q9frwMHDmjs2LHO+PHjx5Wfn6+GhgZt3LhRy5Yt09KlSzVr1qz2OyoAANCpxRhjzJlu/OmnnyotLU3r16/XyJEjFQqF1LdvXy1fvly33nqrJGn37t0aPHiwAoGARowYoTVr1ugnP/mJDhw4IK/XK0lavHix7r//fn366adKTEw86X3q6+tVX1/vvA6Hw8rIyFAoFJLb7T7T6QPfCf0feKWjpxC1j+fkd/QUAJwF4XBYHo/nW/3+btM1KKFQSJKUmpoqSaqsrFRjY6NycnKcmkGDBikzM1OBQECSFAgENHToUCecSFJubq7C4bB27NjR6vuUlpbK4/E4S0ZGRlumDQAALHfGAaW5uVn33nuvrrnmGg0ZMkSSFAwGlZiYqJSUlIhar9erYDDo1Hw9nLSMt4y1pqSkRKFQyFn2799/ptMGAACdQPyZblhUVKTt27fr7bffbs/5tMrlcsnlcp319wEAAHY4ozMoU6dO1erVq/XGG2/ovPPOc9b7fD41NDSorq4uor6mpkY+n8+pOfGunpbXLTUAAOC7LaqAYozR1KlTtXLlSq1bt04DBgyIGB82bJgSEhJUXl7urKuqqlJ1dbX8fr8kye/3a9u2baqtrXVqysrK5Ha7lZWV1ZZjAQAAXURUH/EUFRVp+fLlevHFF9WzZ0/nmhGPx6Nu3brJ4/Fo4sSJKi4uVmpqqtxut6ZNmya/368RI0ZIkkaPHq2srCyNHz9ec+fOVTAY1MyZM1VUVMTHOAAAQFKUAWXRokWSpOuvvz5i/ZIlS/Tzn/9ckjRv3jzFxsaqoKBA9fX1ys3N1cKFC53auLg4rV69WlOmTJHf71f37t01YcIEzZ49u21HAgAAuow2PQelo0RzHzXwXcdzUADY4pw9BwUAAOBsIKAAAADrEFAAAIB1CCgAAMA6BBQAAGAdAgoAALAOAQUAAFiHgAIAAKxDQAEAANYhoAAAAOsQUAAAgHUIKAAAwDoEFAAAYB0CCgAAsA4BBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWIaAAAADrEFAAAIB1CCgAAMA6BBQAAGAdAgoAALAOAQUAAFiHgAIAAKxDQAEAANYhoAAAAOsQUAAAgHUIKAAAwDoEFAAAYB0CCgAAsA4BBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWiTqgvPnmm7r55puVnp6umJgYrVq1KmLcGKNZs2apX79+6tatm3JycrRnz56ImkOHDqmwsFBut1spKSmaOHGijhw50qYDAQAAXUfUAeXo0aO67LLLtGDBglbH586dq/nz52vx4sWqqKhQ9+7dlZubq2PHjjk1hYWF2rFjh8rKyrR69Wq9+eabmjx58pkfBQAA6FLio90gLy9PeXl5rY4ZY/TEE09o5syZGjNmjCTpv/7rv+T1erVq1SqNGzdOu3bt0tq1a7V582YNHz5ckvTkk0/qpptu0mOPPab09PQ2HA4AAOgKog4o32Tfvn0KBoPKyclx1nk8HmVnZysQCGjcuHEKBAJKSUlxwokk5eTkKDY2VhUVFfrpT3960n7r6+tVX1/vvA6Hw+05bQCW6f/AKx09hah9PCe/o6cAdCntepFsMBiUJHm93oj1Xq/XGQsGg0pLS4sYj4+PV2pqqlNzotLSUnk8HmfJyMhoz2kDAADLdIq7eEpKShQKhZxl//79HT0lAABwFrVrQPH5fJKkmpqaiPU1NTXOmM/nU21tbcR4U1OTDh065NScyOVyye12RywAAKDrateAMmDAAPl8PpWXlzvrwuGwKioq5Pf7JUl+v191dXWqrKx0atatW6fm5mZlZ2e353QAAEAnFfVFskeOHNHevXud1/v27dPWrVuVmpqqzMxM3Xvvvfrd736ngQMHasCAAXrwwQeVnp6uW265RZI0ePBg3XjjjZo0aZIWL16sxsZGTZ06VePGjeMOHgAAIOkMAsqWLVv0ox/9yHldXFwsSZowYYKWLl2q++67T0ePHtXkyZNVV1ena6+9VmvXrlVSUpKzzXPPPaepU6dq1KhRio2NVUFBgebPn98OhwMAALqCGGOM6ehJRCscDsvj8SgUCnE9CnAanfGW3c6I24yB04vm93enuIsHAAB8txBQAACAddr1SbIAACBSZ/2YtaM/tuQMCgAAsA4BBQAAWIeAAgAArMM1KEAUOutnyQDQ2XAGBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWIaAAAADrEFAAAIB1CCgAAMA6BBQAAGCd+I6eAAB0Bf0feKWjpxC1j+fkd/QUgFMioADAdxShCjbjIx4AAGAdzqAAADqNznjWB2eGMygAAMA6BBQAAGAdAgoAALAOAQUAAFiHgAIAAKxDQAEAANYhoAAAAOsQUAAAgHUIKAAAwDo8SRYdhidCAgBOhTMoAADAOgQUAABgHQIKAACwDgEFAABYh4ACAACsQ0ABAADWIaAAAADrEFAAAIB1CCgAAMA6BBQAAGAdHnXfRfDYeABAV8IZFAAAYB0CCgAAsA4f8bSCj0sAAOhYHXoGZcGCBerfv7+SkpKUnZ2td955pyOnAwAALNFhAeXPf/6ziouL9dBDD+lvf/ubLrvsMuXm5qq2trajpgQAACzRYQHl8ccf16RJk3TXXXcpKytLixcvVnJysp555pmOmhIAALBEh1yD0tDQoMrKSpWUlDjrYmNjlZOTo0AgcFJ9fX296uvrndehUEiSFA6Hz8r8muu/OCv7BQCgszgbv2Nb9mmMOW1thwSUzz77TMePH5fX641Y7/V6tXv37pPqS0tL9dvf/vak9RkZGWdtjgAAfJd5njh7+z58+LA8Hs831nSKu3hKSkpUXFzsvG5ubtahQ4fUu3dvxcTEdODMzp5wOKyMjAzt379fbre7o6fznUDPOwZ9P/fo+blHz79ijNHhw4eVnp5+2toOCSh9+vRRXFycampqItbX1NTI5/OdVO9yueRyuSLWpaSknM0pWsPtdn+nf5g7Aj3vGPT93KPn5x4912nPnLTokItkExMTNWzYMJWXlzvrmpubVV5eLr/f3xFTAgAAFumwj3iKi4s1YcIEDR8+XFdddZWeeOIJHT16VHfddVdHTQkAAFiiwwLK7bffrk8//VSzZs1SMBjU5ZdfrrVr15504ex3lcvl0kMPPXTSR1s4e+h5x6Dv5x49P/foefRizLe51wcAAOAc4ssCAQCAdQgoAADAOgQUAABgHQIKAACwDgEFAABYh4Byhvr376+YmJiTlqKiIh06dEjTpk3TxRdfrG7duikzM1O/+tWvnC85bFFdXa38/HwlJycrLS1NM2bMUFNTU0TNX//6V1155ZVyuVy66KKLtHTp0pPmsmDBAvXv319JSUnKzs7WO++8EzF+7NgxFRUVqXfv3urRo4cKCgpOeopvZ/BNPZekX/7yl7rwwgvVrVs39e3bV2PGjDnpu53oeXRO1/MWxhjl5eUpJiZGq1atihij59E7Xd+vv/76k8buvvvuiH3Q9+h8m5/1QCCgG264Qd27d5fb7dbIkSP15ZdfOuOHDh1SYWGh3G63UlJSNHHiRB05ciTifd5//3398Ic/VFJSkjIyMjR37tyT5rJixQoNGjRISUlJGjp0qF599dWIcWOMZs2apX79+qlbt27KycnRnj172rkjFjA4I7W1tebgwYPOUlZWZiSZN954w2zbts2MHTvWvPTSS2bv3r2mvLzcDBw40BQUFDjbNzU1mSFDhpicnBzz7rvvmldffdX06dPHlJSUODUfffSRSU5ONsXFxWbnzp3mySefNHFxcWbt2rVOzfPPP28SExPNM888Y3bs2GEmTZpkUlJSTE1NjVNz9913m4yMDFNeXm62bNliRowYYa6++upz06h29E09N8aYp556yqxfv97s27fPVFZWmptvvtlkZGSYpqYmYww9PxOn63mLxx9/3OTl5RlJZuXKlc56en5mTtf36667zkyaNCmiJhQKOdvT9+idrucbN240brfblJaWmu3bt5vdu3ebP//5z+bYsWPOPm688UZz2WWXmU2bNpm33nrLXHTRReaOO+5wxkOhkPF6vaawsNBs377d/OlPfzLdunUzTz31lFOzYcMGExcXZ+bOnWt27txpZs6caRISEsy2bducmjlz5hiPx2NWrVpl3nvvPfMv//IvZsCAAebLL788+406hwgo7eSee+4xF154oWlubm51/IUXXjCJiYmmsbHRGGPMq6++amJjY00wGHRqFi1aZNxut6mvrzfGGHPfffeZSy65JGI/t99+u8nNzXVeX3XVVaaoqMh5ffz4cZOenm5KS0uNMcbU1dWZhIQEs2LFCqdm165dRpIJBAJtPOqOdbqev/fee0aS2bt3rzGGnreH1nr+7rvvmu9973vm4MGDJwUUet4+Tuz7ddddZ+65555T1tP3tjux59nZ2WbmzJmnrN+5c6eRZDZv3uysW7NmjYmJiTH/+Mc/jDHGLFy40PTq1cv5OzDGmPvvv99cfPHFzuvbbrvN5OfnR+w7Ozvb/PKXvzTGGNPc3Gx8Pp/5/e9/74zX1dUZl8tl/vSnP7XhiO3DRzztoKGhQc8++6x+8YtfnPLblUOhkNxut+Ljv3p4byAQ0NChQyOenJubm6twOKwdO3Y4NTk5ORH7yc3NVSAQcN63srIyoiY2NlY5OTlOTWVlpRobGyNqBg0apMzMTKemMzpdz48ePaolS5ZowIABysjIkETP26q1nn/xxRe68847tWDBgla/6JOet92pftafe+459enTR0OGDFFJSYm++OILZ4y+t82JPa+trVVFRYXS0tJ09dVXy+v16rrrrtPbb7/tbBMIBJSSkqLhw4c763JychQbG6uKigqnZuTIkUpMTHRqcnNzVVVVpX/+859OzTf9vezbt0/BYDCixuPxKDs7u1P3vDUElHawatUq1dXV6ec//3mr45999pkeeeQRTZ482VkXDAZPeqx/y+tgMPiNNeFwWF9++aU+++wzHT9+vNWar+8jMTHxpG9//npNZ3Sqni9cuFA9evRQjx49tGbNGpWVlTn/MaDnbdNaz6dPn66rr75aY8aMaXUbet52rfX9zjvv1LPPPqs33nhDJSUl+u///m/927/9mzNO39vmxJ5/9NFHkqSHH35YkyZN0tq1a3XllVdq1KhRzrUfwWBQaWlpEfuJj49XamrqaXveMvZNNV8f//p2rdV0FR32XTxdydNPP628vDylp6efNBYOh5Wfn6+srCw9/PDD535yXdSpel5YWKgf//jHOnjwoB577DHddttt2rBhg5KSkjpopl3HiT1/6aWXtG7dOr377rsdPLOurbWf9a//z87QoUPVr18/jRo1Sh9++KEuvPDCjphml3Jiz5ubmyV9dSF+yxfaXnHFFSovL9czzzyj0tLSDptrV8YZlDb6+9//rtdff13//u//ftLY4cOHdeONN6pnz55auXKlEhISnDGfz3fSle4tr1tOlZ+qxu12q1u3burTp4/i4uJarfn6PhoaGlRXV3fKms7mm3ru8Xg0cOBAjRw5Uv/zP/+j3bt3a+XKlZLoeVu01vN169bpww8/VEpKiuLj452PLwsKCnT99ddLoudt9U0/61+XnZ0tSdq7d68k+t4WrfW8X79+kqSsrKyI2sGDB6u6ulrSV72ora2NGG9qatKhQ4dO2/OWsW+q+fr417drraarIKC00ZIlS5SWlqb8/PyI9eFwWKNHj1ZiYqJeeumlk/4P3u/3a9u2bRE/0GVlZXK73c4/Ar/fr/Ly8ojtysrK5Pf7JUmJiYkaNmxYRE1zc7PKy8udmmHDhikhISGipqqqStXV1U5NZ3Oqnp/IfHURuOrr6yXR87ZorecPPPCA3n//fW3dutVZJGnevHlasmSJJHreVt/2Z72l9y2/SOn7mWut5/3791d6erqqqqoiaj/44AOdf/75kr7qZ11dnSorK53xdevWqbm52QmQfr9fb775phobG52asrIyXXzxxerVq5dT801/LwMGDJDP54uoCYfDqqio6LQ9P6WOvkq3Mzt+/LjJzMw0999/f8T6UChksrOzzdChQ83evXsjbl078ZbX0aNHm61bt5q1a9eavn37tnob4IwZM8yuXbvMggULWr0N0OVymaVLl5qdO3eayZMnm5SUlIir9++++26TmZlp1q1bZ7Zs2WL8fr/x+/1nuTtnx6l6/uGHH5pHH33UbNmyxfz97383GzZsMDfffLNJTU11bomk52fmVD1vjU5xmzE9j96p+r53714ze/Zss2XLFrNv3z7z4osvmgsuuMCMHDnSqaHvZ+abftbnzZtn3G63WbFihdmzZ4+ZOXOmSUpKcu4SNOar24yvuOIKU1FRYd5++20zcODAiNuM6+rqjNfrNePHjzfbt283zz//vElOTj7pNuP4+Hjz2GOPmV27dpmHHnqo1duMU1JSzIsvvmjef/99M2bMGG4zRqTXXnvNSDJVVVUR69944w0jqdVl3759Tt3HH39s8vLyTLdu3UyfPn3Mr3/9a+c25K/v6/LLLzeJiYnmggsuMEuWLDlpHk8++aTJzMw0iYmJ5qqrrjKbNm2KGP/yyy/Nf/zHf5hevXqZ5ORk89Of/tQcPHiw3fpwLp2q5//4xz9MXl6eSUtLMwkJCea8884zd955p9m9e3dEHT2P3ql63poTA4ox9PxMnarv1dXVZuTIkSY1NdW4XC5z0UUXmRkzZkQ8B8UY+n4mTvezXlpaas477zyTnJxs/H6/eeuttyLGP//8c3PHHXeYHj16GLfbbe666y5z+PDhiJr33nvPXHvttcblcpnvfe97Zs6cOSe9zwsvvGC+//3vm8TERHPJJZeYV155JWK8ubnZPPjgg8br9RqXy2VGjRr1rf59djYxxhjTIaduAAAAToFrUAAAgHUIKAAAwDoEFAAAYB0CCgAAsA4BBQAAWIeAAgAArENAAQAA1iGgAAAA6xBQAACAdQgoAADAOgQUAABgnf8PnAKZK2Zx6/cAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\")\n",
    "#previously, we went from most-used to least-used CCB vtds until each has unit use\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "CCBuse = [0. for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    minCCBuse = float(input(\"enter target CCBuse for CCB \"+str(j)+\" I reco 1.02, as we may lose a little later\"))\n",
    "    postCCBaddPops = list()\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    #ccbNbrSet = set(unitNbrs[unitNo])\n",
    "    #ccbFrac = [-1.*CCBpopFrac[t][j] for t in range(nHDs) ]  # -1 to go from most- to least-used\n",
    "    #idx = np.argsort(ccbFrac)\n",
    "    preCCBpop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in CCBaddCandidates[j]]\n",
    "    idx = np.argsort(preCCBpop)\n",
    "    i = 0\n",
    "    t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "    while CCBuse[j] < minCCBuse  and i < len(CCBaddCandidates[j]) :  #and CCBpopFrac[t][j] > 0:\n",
    "        t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        HDunitList[t].append(unitNo)\n",
    "        postCCBaddPops.append(np.sum([unitPop[u] for u in HDunitList[t] ]))\n",
    "        i +=1\n",
    "    unitUse[unitNo] = CCBuse[j]\n",
    "    print(\"final unit use of CCB\",j, \"is\",r5(CCBuse[j]),\"; here is a histogram of HDpop using this CCB\")\n",
    "    plt.hist(postCCBaddPops)\n",
    "    plt.axvline(aDP,ls=\"--\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf747d9c-cf6d-420e-9c3c-6723619586ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#end of preliminaries for \"option 3\" - converting HDtractlists to unit lists instead of option 2's geometric probing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26102ca2-79c1-48db-b873-7fa3a1553911",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "dc26d08c-a5d9-4e7e-9da5-ae98cf658a3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.01276 0.1213\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "print(\"Here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t] / aDP for t in range(nHDs) ], bins=20, weights = HDweight, label= \"HDpop / target\" )\n",
    "plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53e4c298-e6cb-4fee-a511-b8f6c3940539",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "c4183011-724a-4014-8c94-f9f9382c7e75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Did I grossly overuse any units, or skip any live ones?\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "above: underused < 0.5; below overused > 1.6\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Did I grossly overuse any units, or skip any live ones?\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5 and unitPop[u] > 5:\n",
    "        plotPoly(unitGeom[u])\n",
    "        #print(u,unitPop[u], unitUse[u])\n",
    "        #for c in range(nCounties):\n",
    "        #    if u in countyUnitList[c]:\n",
    "        #        print(u,\"is in county\",c)\n",
    "        #        print(\"its neighbor units are\",unitNbrs[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"above: underused < 0.5; below overused > 1.6\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 1.6:\n",
    "        plotPoly(unitGeom[u],0.3)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ce9292b0-7d6a-419a-9491-d0def779ad04",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 7057 populated HDs out of 7059\n"
     ]
    }
   ],
   "source": [
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "populatedTractList = popHDlist.copy()\n",
    "print(\"there are a total of\",len(populatedTractList),\"populated HDs out of\",nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f7f36559-7f1d-4203-8b24-0e8cc2ce1753",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this will show if we had any duplicated units in HDunitLists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this will show if we had any duplicated units in HDunitLists\")\n",
    "excess = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    excess[t] = len(HDunitList[t]) - len(set(HDunitList[t]))\n",
    "plt.hist(excess)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "27bc7f0a-d7ff-4c68-830f-29ba5013c314",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#popHDlist = populatedTractList.copy()  #somehow our popHDlist started to include the cut District HD starters\n",
    "HDunitList = [list(set(HDunitList[t])) for t in range(nHDs)]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "af8a4945-40c2-40df-8dd4-d516f4de2f0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 240\n",
      "working on HD 1400 time is now 514\n",
      "working on HD 2100 time is now 750\n",
      "working on HD 2800 time is now 1002\n",
      "working on HD 3500 time is now 1243\n",
      "working on HD 4202 time is now 1516\n",
      "working on HD 4902 time is now 1740\n",
      "working on HD 5602 time is now 1978\n",
      "working on HD 6302 time is now 2252\n",
      "working on HD 7002 time is now 2481\n",
      "out of 7057 total HDs, there were 1247.0 contiguous and 561.0 complement-contiguous HDs\n",
      "5425 HDs had both discontiguity problems, while enclave-only = 1071 and discontig only= 385\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 5810 1071\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "40f06e44-45be-4a36-b62c-26698af70e06",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 699879 district pop vs 736714 target\n",
      "we'll also trim any HD with total islands' pop <= 14734\n",
      "working on HD 0\n",
      "working on HD 250\n",
      "working on HD 477\n",
      "working on HD 706\n",
      "working on HD 954\n",
      "working on HD 1183\n",
      "working on HD 1434\n",
      "working on HD 1675\n",
      "working on HD 1920\n",
      "working on HD 2161\n",
      "working on HD 2391\n",
      "working on HD 2627\n",
      "working on HD 2876\n",
      "working on HD 3116\n",
      "working on HD 3340\n",
      "working on HD 3614\n",
      "working on HD 3848\n",
      "working on HD 4075\n",
      "working on HD 4296\n",
      "working on HD 4536\n",
      "working on HD 4782\n",
      "working on HD 5011\n",
      "working on HD 5262\n",
      "working on HD 5581\n",
      "working on HD 5809\n",
      "working on HD 6041\n",
      "working on HD 6308\n",
      "working on HD 6573\n",
      "working on HD 6806\n",
      "working on HD 7046\n",
      "Out of 5810 discontig HDs 5810 had discontig HDs.\n",
      "Of these, 5729 won't be under 699879 after all minor discontigys were shed, while 81 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "reclassifying HD 0\n",
      "reclassifying HD 599\n",
      "reclassifying HD 1183\n",
      "reclassifying HD 1802\n",
      "reclassifying HD 2391\n",
      "reclassifying HD 2999\n",
      "reclassifying HD 3614\n",
      "reclassifying HD 4189\n",
      "reclassifying HD 4782\n",
      "reclassifying HD 5418\n",
      "reclassifying HD 6041\n",
      "reclassifying HD 6697\n",
      "There are 81 HDs still with both discontinuity problems\n",
      "Additionally, 5346 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%200 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for i, t in enumerate(sPgenerator):    \n",
    "    if i%500 == 0:\n",
    "        print(\"reclassifying HD\",t)\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4037f8cb-661b-4032-bfb9-e147975e3bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classify further: ID those with adjoiners intersecting the map boundary vs internal islands\n",
      "working on enclave-generating HD 3 0 seconds elapsed\n",
      "working on enclave-generating HD 3499 15 seconds elapsed\n",
      "working on enclave-generating HD 6538 26 seconds elapsed\n",
      "working on enclave-generating HD 566 40 seconds elapsed\n",
      "working on enclave-generating HD 1191 57 seconds elapsed\n",
      "working on enclave-generating HD 1870 77 seconds elapsed\n",
      "working on enclave-generating HD 2538 95 seconds elapsed\n",
      "working on enclave-generating HD 3188 111 seconds elapsed\n",
      "working on enclave-generating HD 3854 125 seconds elapsed\n",
      "working on enclave-generating HD 4447 141 seconds elapsed\n",
      "working on enclave-generating HD 5089 160 seconds elapsed\n",
      "working on enclave-generating HD 5828 176 seconds elapsed\n",
      "working on enclave-generating HD 6507 194 seconds elapsed\n",
      "Out of 6417 HDpolys that generated enclaves, 0 had contiguous adjrs, while 5783 neighbored a state boundary while 634 had only internal enclaves\n"
     ]
    }
   ],
   "source": [
    "print(\"Classify further: ID those with adjoiners intersecting the map boundary vs internal islands\")\n",
    "internals, edgers, nOK = list(), list(), 0\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(eLgenerator):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on enclave-generating HD\",t,int(time.time()-startTime),\"seconds elapsed\")\n",
    "    twoNbrs = get2nbrs(HDunitList[t],unitNbrs)\n",
    "    isContig, adjSublist = isContiguous(twoNbrs,unitNbrs)\n",
    "    if isContig:\n",
    "        nOK +=1\n",
    "    else:\n",
    "        if len (set(getAdjoiners(HDunitList[t],unitNbrs)).intersection(set(borderUnits)))  > 0:\n",
    "            edgers.append(t)\n",
    "        else:\n",
    "            internals.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDpolys that generated enclaves,\",nOK,\"had contiguous adjrs, while\",len(edgers),\n",
    "      \"neighbored a state boundary while\",len(internals),\"had only internal enclaves\")   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "05f929ce-4f94-47a6-baf4-60c5a89e2ae5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 773550 district pop vs 736714 target\n",
      "working on enclave-y HD 662 . We have evaluated 0 of 6417 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 1545 . We have evaluated 200 of 6417 enclavy HDs.Time is now 208\n",
      "working on enclave-y HD 4195 . We have evaluated 400 of 6417 enclavy HDs.Time is now 416\n",
      "working on enclave-y HD 6730 . We have evaluated 600 of 6417 enclavy HDs.Time is now 584\n",
      "working on enclave-y HD 1310 . We have evaluated 800 of 6417 enclavy HDs.Time is now 694\n",
      "working on enclave-y HD 2761 . We have evaluated 1000 of 6417 enclavy HDs.Time is now 792\n",
      "working on enclave-y HD 4453 . We have evaluated 1200 of 6417 enclavy HDs.Time is now 886\n",
      "working on enclave-y HD 5516 . We have evaluated 1400 of 6417 enclavy HDs.Time is now 966\n",
      "working on enclave-y HD 6853 . We have evaluated 1600 of 6417 enclavy HDs.Time is now 1052\n",
      "working on enclave-y HD 250 . We have evaluated 1800 of 6417 enclavy HDs.Time is now 1142\n",
      "working on enclave-y HD 490 . We have evaluated 2000 of 6417 enclavy HDs.Time is now 1274\n",
      "working on enclave-y HD 744 . We have evaluated 2200 of 6417 enclavy HDs.Time is now 1420\n",
      "working on enclave-y HD 1050 . We have evaluated 2400 of 6417 enclavy HDs.Time is now 1540\n",
      "working on enclave-y HD 1340 . We have evaluated 2600 of 6417 enclavy HDs.Time is now 1670\n",
      "working on enclave-y HD 1711 . We have evaluated 2800 of 6417 enclavy HDs.Time is now 1822\n",
      "working on enclave-y HD 2014 . We have evaluated 3000 of 6417 enclavy HDs.Time is now 1921\n",
      "working on enclave-y HD 2272 . We have evaluated 3200 of 6417 enclavy HDs.Time is now 2036\n",
      "working on enclave-y HD 2548 . We have evaluated 3400 of 6417 enclavy HDs.Time is now 2204\n",
      "working on enclave-y HD 2826 . We have evaluated 3600 of 6417 enclavy HDs.Time is now 2315\n",
      "working on enclave-y HD 3112 . We have evaluated 3800 of 6417 enclavy HDs.Time is now 2447\n",
      "working on enclave-y HD 3426 . We have evaluated 4000 of 6417 enclavy HDs.Time is now 2531\n",
      "working on enclave-y HD 3749 . We have evaluated 4200 of 6417 enclavy HDs.Time is now 2636\n",
      "working on enclave-y HD 4018 . We have evaluated 4400 of 6417 enclavy HDs.Time is now 2753\n",
      "working on enclave-y HD 4296 . We have evaluated 4600 of 6417 enclavy HDs.Time is now 2892\n",
      "working on enclave-y HD 4564 . We have evaluated 4800 of 6417 enclavy HDs.Time is now 2985\n",
      "working on enclave-y HD 4857 . We have evaluated 5000 of 6417 enclavy HDs.Time is now 3094\n",
      "working on enclave-y HD 5112 . We have evaluated 5200 of 6417 enclavy HDs.Time is now 3270\n",
      "working on enclave-y HD 5462 . We have evaluated 5400 of 6417 enclavy HDs.Time is now 3380\n",
      "working on enclave-y HD 5821 . We have evaluated 5600 of 6417 enclavy HDs.Time is now 3521\n",
      "working on enclave-y HD 6097 . We have evaluated 5800 of 6417 enclavy HDs.Time is now 3634\n",
      "working on enclave-y HD 6448 . We have evaluated 6000 of 6417 enclavy HDs.Time is now 3767\n",
      "working on enclave-y HD 6734 . We have evaluated 6200 of 6417 enclavy HDs.Time is now 3899\n",
      "working on enclave-y HD 7033 . We have evaluated 6400 of 6417 enclavy HDs.Time is now 4019\n",
      "Out of 6417 HDs with enclaves 6417 had enclaves.\n",
      "Of these, 6142 wouldn't be over 773550 if all enclaves filled, while 275 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(internals + edgers):\n",
    "    if iii%200 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8987ad1f-d372-415d-a2ec-8fc6736c5102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "634 5783 5425 4788\n",
      "275 275 6142\n"
     ]
    }
   ],
   "source": [
    "print(len(internals),len(edgers),len(doubleTroubleList),len(set(edgers).intersection(set(doubleTroubleList))))\n",
    "print(len(set(edgers).difference(set(canFill))) ,len(cantFill) , len(canFill))\n",
    "#610 3379 2187 1954\n",
    "#80 80 3909  for original MN option3 (assigned CCBs by captured area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "8fa887be-92e6-422a-8e80-e00fd3265aab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01365 0.12103\n",
      "CCB cluster 0 = unit 6836 with pop 13737.0 now has use of 1.0207084899548922\n",
      "CCB cluster 1 = unit 6837 with pop 169151.0 now has use of 1.0204736636533835\n",
      "CCB cluster 2 = unit 6838 with pop 171003.0 now has use of 1.020031158599702\n",
      "CCB cluster 3 = unit 6839 with pop 92501.0 now has use of 1.0171955970747164\n",
      "CCB cluster 4 = unit 6840 with pop 51938.0 now has use of 1.0269266361234095\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "e9d50ef8-39b2-4e22-a11e-cabeda78721e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "b759b3c7-b8a3-4d2c-a8fe-50fa93b3e940",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "551454fb-d57c-466f-8b31-39ccb2a728de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 275 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "for t in cantFill:\n",
    "    plotPoly(hdCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "5269a224-4a97-417c-99af-6a98df0087ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the barredJettisonSet (cannot be shed in below MUSTFREE code) is {6836, 6837, 6838, 6839, 6840}\n",
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n",
      "working on avg unit-to-HDcp dist for HD 3200\n",
      "working on avg unit-to-HDcp dist for HD 4002\n",
      "working on avg unit-to-HDcp dist for HD 4802\n",
      "working on avg unit-to-HDcp dist for HD 5602\n",
      "working on avg unit-to-HDcp dist for HD 6402\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set(list())\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u]% 1 > 0.23 and allUnits[u]%1 < 0.27:\n",
    "        barredJettisonSet.add(u)\n",
    "print(\"the barredJettisonSet (cannot be shed in below MUSTFREE code) is\",barredJettisonSet)\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6e2e44bd-a084-42f6-b533-5dc6d21912a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 275 HDs\n",
      "working on HD 166 cantFill 0 of 275 .Time is now 0\n",
      "working on HD 2602 cantFill 20 of 275 .Time is now 1\n",
      "working on HD 6813 cantFill 40 of 275 .Time is now 3\n",
      "working on HD 523 cantFill 60 of 275 .Time is now 6\n",
      "working on HD 949 cantFill 80 of 275 .Time is now 7\n",
      "working on HD 1154 cantFill 100 of 275 .Time is now 9\n",
      "working on HD 2340 cantFill 120 of 275 .Time is now 11\n",
      "working on HD 2574 cantFill 140 of 275 .Time is now 13\n",
      "working on HD 2619 cantFill 160 of 275 .Time is now 14\n",
      "working on HD 3509 cantFill 180 of 275 .Time is now 16\n",
      "working on HD 4363 cantFill 200 of 275 .Time is now 19\n",
      "working on HD 4634 cantFill 220 of 275 .Time is now 22\n",
      "working on HD 5783 cantFill 240 of 275 .Time is now 24\n",
      "working on HD 6825 cantFill 260 of 275 .Time is now 27\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.01227 0.1214\n",
      "CCB cluster 0 = unit 6836 with pop 13737.0 now has use of 1.0062836396312103\n",
      "CCB cluster 1 = unit 6837 with pop 169151.0 now has use of 1.0175118660241111\n",
      "CCB cluster 2 = unit 6838 with pop 171003.0 now has use of 1.0123836939602349\n",
      "CCB cluster 3 = unit 6839 with pop 92501.0 now has use of 1.0171955970747164\n",
      "CCB cluster 4 = unit 6840 with pop 51938.0 now has use of 1.0269266361234095\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66e91b98-63a9-47db-af63-039ac47b1835",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "ca9ce3cb-c150-4f39-ae55-f781d39d7f57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "postMustFreeUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "c32dd108-073b-48aa-99ce-fea50c8d023c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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cLpcWLlyo0tJS7dmzx3msqVOnqq6uThs3bjyjuYXDYXm9XtXX18vj8XT2KQLoooYsKo32FDrsraWBaE8B6PLO9Pv3Wb0Hpr6+XpLUr18/SVJFRYWampqUm5vrjBk+fLgyMjIUDAYlScFgUNnZ2U68SFJeXp7C4bD27t3rjDn5GK1jWo/RloaGBoXD4YgbAADonjodMC0tLZo7d64++9nPauTIkZKkUCgkl8ul5OTkiLGpqakKhULOmJPjpXV/676PGxMOh3Xs2LE257NkyRJ5vV7nlp6e3tmnBgAAurhOB0xhYaH27NmjtWvXnsv5dFpxcbHq6+ud28GDB6M9JQAAcJ7Ed+ZOc+bM0YYNG7Rt2zYNGjTI2e7z+dTY2Ki6urqIV2Fqamrk8/mcMTt27Ig4XuunlE4e89FPLtXU1Mjj8SgxMbHNObndbrnd7s48HQAAYJkOvQJjjNGcOXP0zDPPaPPmzcrMzIzYn5OTo169eqm8vNzZVlVVperqavn9fkmS3+/X7t27VVtb64wpKyuTx+NRVlaWM+bkY7SOaT0GAADo2Tr0CkxhYaHWrFmj5557Tn369HHes+L1epWYmCiv16uZM2eqqKhI/fr1k8fj0e233y6/369x48ZJkiZOnKisrCxNmzZNy5YtUygU0l133aXCwkLnFZTZs2froYce0oIFCzRjxgxt3rxZ69atU2mpfZ86AAAA516HXoFZuXKl6uvr9YUvfEEDBw50bk899ZQz5oEHHtC1116r/Px8jR8/Xj6fT08//bSzPy4uThs2bFBcXJz8fr++853v6MYbb9Q999zjjMnMzFRpaanKyso0atQo3X///XrssceUl5d3Dp4yAACw3VldB6Yr4zowQPfGdWCA7umCXAcGAAAgGggYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANaJj/YEAKCnGLKoNNpT6LC3lgaiPQWgTbwCAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArNPhgNm2bZu+8pWvKC0tTTExMXr22Wcj9htjtHjxYg0cOFCJiYnKzc3V66+/HjHm8OHDKigokMfjUXJysmbOnKn3338/Ysyrr76qz33uc0pISFB6erqWLVvW8WcHAAC6pQ4HzNGjRzVq1CitWLGizf3Lli3Tgw8+qFWrVmn79u266KKLlJeXp+PHjztjCgoKtHfvXpWVlWnDhg3atm2bbr31Vmd/OBzWxIkTNXjwYFVUVOi+++7TT37yEz366KOdeIoAAKC7iTHGmE7fOSZGzzzzjL72ta9J+vDVl7S0NP3gBz/QD3/4Q0lSfX29UlNTVVJSoqlTp+q1115TVlaWdu7cqTFjxkiSNm7cqC9/+cv673//q7S0NK1cuVJ33nmnQqGQXC6XJGnRokV69tlntX///jOaWzgcltfrVX19vTweT2efIoAuasii0mhPoUd4a2kg2lNAD3Om37/P6XtgDhw4oFAopNzcXGeb1+vV2LFjFQwGJUnBYFDJyclOvEhSbm6uYmNjtX37dmfM+PHjnXiRpLy8PFVVVem9995r87EbGhoUDocjbgAAoHs6pwETCoUkSampqRHbU1NTnX2hUEgpKSkR++Pj49WvX7+IMW0d4+TH+KglS5bI6/U6t/T09LN/QgAAoEvqNp9CKi4uVn19vXM7ePBgtKcEAADOk3MaMD6fT5JUU1MTsb2mpsbZ5/P5VFtbG7H/xIkTOnz4cMSYto5x8mN8lNvtlsfjibgBAIDu6ZwGTGZmpnw+n8rLy51t4XBY27dvl9/vlyT5/X7V1dWpoqLCGbN582a1tLRo7Nixzpht27apqanJGVNWVqZhw4apb9++53LKAADAQh0OmPfff1+VlZWqrKyU9OEbdysrK1VdXa2YmBjNnTtXP//5z/XHP/5Ru3fv1o033qi0tDTnk0ojRozQpEmTNGvWLO3YsUN///vfNWfOHE2dOlVpaWmSpG9/+9tyuVyaOXOm9u7dq6eeekrLly9XUVHROXviAADAXvEdvcOuXbt0zTXXOF+3RsX06dNVUlKiBQsW6OjRo7r11ltVV1enq6++Whs3blRCQoJzn9WrV2vOnDmaMGGCYmNjlZ+frwcffNDZ7/V69ac//UmFhYXKycnRgAEDtHjx4ohrxQAAgJ7rrK4D05VxHRige+M6MBcG14HBhRaV68AAAABcCAQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKwTH+0JAAC6riGLSqM9hQ57a2kg2lPABcArMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKxDwAAAAOsQMAAAwDoEDAAAsA4BAwAArEPAAAAA6xAwAADAOgQMAACwDgEDAACsQ8AAAADrEDAAAMA6BAwAALAOAQMAAKwTH+0JAABwLg1ZVBrtKXTYW0sD0Z6CdXgFBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYB0CBgAAWIffRg3Ayt/eC6Bn4xUYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHW4kB1wjnFROAAdZeN5462lgag+Pq/AAAAA6xAwAADAOl06YFasWKEhQ4YoISFBY8eO1Y4dO6I9JQAA0AV02YB56qmnVFRUpLvvvlv/+Mc/NGrUKOXl5am2tjbaUwMAAFHWZQPmV7/6lWbNmqWbb75ZWVlZWrVqlZKSkvT73/8+2lMDAABR1iU/hdTY2KiKigoVFxc722JjY5Wbm6tgMNjmfRoaGtTQ0OB8XV9fL0kKh8Pnd7LAR7Q0fBDtKQDAeXe+vr+2HtcY87HjumTA/N///Z+am5uVmpoasT01NVX79+9v8z5LlizRT3/601O2p6enn5c5AgDQk3l/fX6Pf+TIEXm93tPu75IB0xnFxcUqKipyvm5padHhw4fVv39/xcTERHFmXVs4HFZ6eroOHjwoj8cT7elYgTXrONasc1i3jmPNOqcrrZsxRkeOHFFaWtrHjuuSATNgwADFxcWppqYmYntNTY18Pl+b93G73XK73RHbkpOTz9cUux2PxxP1v7S2Yc06jjXrHNat41izzukq6/Zxr7y06pJv4nW5XMrJyVF5ebmzraWlReXl5fL7/VGcGQAA6Aq65CswklRUVKTp06drzJgxuuqqq/TrX/9aR48e1c033xztqQEAgCjrsgFzww036J133tHixYsVCoV0xRVXaOPGjae8sRdnx+126+677z7lx284Pdas41izzmHdOo416xwb1y3GtPc5JQAAgC6mS74HBgAA4OMQMAAAwDoEDAAAsA4BAwAArEPAdHH/+9//9J3vfEf9+/dXYmKisrOztWvXLme/MUaLFy/WwIEDlZiYqNzcXL3++usRxzh8+LAKCgrk8XiUnJysmTNn6v33348Y8+qrr+pzn/ucEhISlJ6ermXLlp0yl/Xr12v48OFKSEhQdna2XnjhhYj9ZzKXC6W9dbvpppsUExMTcZs0aVLEMXrSug0ZMuSU9YiJiVFhYaEk6fjx4yosLFT//v3Vu3dv5efnn3KhyerqagUCASUlJSklJUXz58/XiRMnIsZs2bJFo0ePltvt1tChQ1VSUnLKXFasWKEhQ4YoISFBY8eO1Y4dOyL2n8lcLpT21u0LX/jCKftmz54dcYyetm7Nzc368Y9/rMzMTCUmJurSSy/Vz372s4jfe8N5LdKZrFmPPKcZdFmHDx82gwcPNjfddJPZvn27efPNN82mTZvMG2+84YxZunSp8Xq95tlnnzWvvPKK+epXv2oyMzPNsWPHnDGTJk0yo0aNMi+//LL561//aoYOHWq+9a1vOfvr6+tNamqqKSgoMHv27DF/+MMfTGJionnkkUecMX//+99NXFycWbZsmdm3b5+56667TK9evczu3bs7NJcL4UzWbfr06WbSpEnm7bffdm6HDx+OOE5PWrfa2tqItSgrKzOSzF/+8hdjjDGzZ8826enppry83OzatcuMGzfOfOYzn3Huf+LECTNy5EiTm5tr/vnPf5oXXnjBDBgwwBQXFztj3nzzTZOUlGSKiorMvn37zG9+8xsTFxdnNm7c6IxZu3atcblc5ve//73Zu3evmTVrlklOTjY1NTXOmPbmciG1t26f//znzaxZsyLG1NfXO/fviet27733mv79+5sNGzaYAwcOmPXr15vevXub5cuXO2M4r0U6kzXriec0AqYLW7hwobn66qtPu7+lpcX4fD5z3333Odvq6uqM2+02f/jDH4wxxuzbt89IMjt37nTGvPjiiyYmJsb873//M8YY8/DDD5u+ffuahoaGiMceNmyY8/U3v/lNEwgEIh5/7Nix5rvf/e4Zz+VCaW/djPnwH/t111132v09cd1Odscdd5hLL73UtLS0mLq6OtOrVy+zfv16Z/9rr71mJJlgMGiMMeaFF14wsbGxJhQKOWNWrlxpPB6Psz4LFiwwl112WcTj3HDDDSYvL8/5+qqrrjKFhYXO183NzSYtLc0sWbLEGGPOaC7RdPK6GfNhwNxxxx2nHd8T1y0QCJgZM2ZEbJsyZYopKCgwxnBea0t7a2ZMzzyn8SOkLuyPf/yjxowZo2984xtKSUnRlVdeqd/+9rfO/gMHDigUCik3N9fZ5vV6NXbsWAWDQUlSMBhUcnKyxowZ44zJzc1VbGystm/f7owZP368XC6XMyYvL09VVVV67733nDEnP07rmNbHOZO5XCjtrVurLVu2KCUlRcOGDdNtt92md99919nXE9etVWNjo5588knNmDFDMTExqqioUFNTU8Qchw8froyMjIi/Z9nZ2REXmszLy1M4HNbevXudMR+3Fo2NjaqoqIgYExsbq9zcXGfMmcwlWj66bq1Wr16tAQMGaOTIkSouLtYHH3zg7OuJ6/aZz3xG5eXl+te//iVJeuWVV/S3v/1NkydPlsR5rS3trVmrnnZO67JX4oX05ptvauXKlSoqKtKPfvQj7dy5U9///vflcrk0ffp0hUIhSTrl6sSpqanOvlAopJSUlIj98fHx6tevX8SYzMzMU47Ruq9v374KhULtPk57c7lQ2ls3SZo0aZKmTJmizMxM/fvf/9aPfvQjTZ48WcFgUHFxcT1y3Vo9++yzqqur00033STpwzm6XK5TfjnqR59HW8+hdd/HjQmHwzp27Jjee+89NTc3tzlm//79ZzyXaPnouknSt7/9bQ0ePFhpaWl69dVXtXDhQlVVVenpp5+W1DPXbdGiRQqHwxo+fLji4uLU3Nyse++9VwUFBc5cW+d2urn2tH+f7a2Z1DPPaQRMF9bS0qIxY8boF7/4hSTpyiuv1J49e7Rq1SrnGzFOdSbrNnXqVGd8dna2Lr/8cl166aXasmWLJkyYEJV5dxW/+93vNHny5HZ/lT0itbVut956q/Pn7OxsDRw4UBMmTNC///1vXXrppdGYZtStW7dOq1ev1po1a3TZZZepsrJSc+fOVVpaGue10ziTNeuJ5zR+hNSFDRw4UFlZWRHbRowYoerqakmSz+eTpFM+SVBTU+Ps8/l8qq2tjdh/4sQJHT58OGJMW8c4+TFON+bk/e3N5UJpb93acskll2jAgAF64403JPXMdZOk//znP/rzn/+sW265xdnm8/nU2Niourq6iLEffR6dXQuPx6PExEQNGDBAcXFx7a5Xe3OJhrbWrS1jx46VpIi/Zz1t3ebPn69FixZp6tSpys7O1rRp0zRv3jwtWbLEmWvr3E43157277O9NWtLTzinETBd2Gc/+1lVVVVFbPvXv/6lwYMHS5IyMzPl8/lUXl7u7A+Hw9q+fbv8fr8kye/3q66uThUVFc6YzZs3q6WlxTmZ+v1+bdu2TU1NTc6YsrIyDRs2TH379nXGnPw4rWNaH+dM5nKhtLdubfnvf/+rd999VwMHDpTUM9dNkh5//HGlpKQoEAg423JyctSrV6+IOVZVVam6ujri79nu3bsjTpBlZWXyeDxOTLa3Fi6XSzk5ORFjWlpaVF5e7ow5k7lEQ1vr1pbKykpJivh71tPW7YMPPlBsbOS3nri4OLW0tEjivNaW9tasLT3inHZO3xKMc2rHjh0mPj7e3Hvvveb11183q1evNklJSebJJ590xixdutQkJyeb5557zrz66qvmuuuua/PjhldeeaXZvn27+dvf/mY++clPRnx0rq6uzqSmpppp06aZPXv2mLVr15qkpKRTPjoXHx9vfvnLX5rXXnvN3H333W1+dK69uVwI7a3bkSNHzA9/+EMTDAbNgQMHzJ///GczevRo88lPftIcP37cOU5PW7fm5maTkZFhFi5ceMq+2bNnm4yMDLN582aza9cu4/f7jd/vd/a3fhx44sSJprKy0mzcuNFcfPHFbX4ceP78+ea1114zK1asaPPjwG6325SUlJh9+/aZW2+91SQnJ0d8Sqe9uVxop1u3N954w9xzzz1m165d5sCBA+a5554zl1xyiRk/frwzpieu2/Tp080nPvEJ5yPBTz/9tBkwYIBZsGCBM4bzWqT21qynntMImC7u+eefNyNHjjRut9sMHz7cPProoxH7W1pazI9//GOTmppq3G63mTBhgqmqqooY8+6775pvfetbpnfv3sbj8Zibb77ZHDlyJGLMK6+8Yq6++mrjdrvNJz7xCbN06dJT5rJu3TrzqU99yrhcLnPZZZeZ0tLSDs/lQvm4dfvggw/MxIkTzcUXX2x69eplBg8ebGbNmhVxsjem563bpk2bjKQ2H/vYsWPme9/7nunbt69JSkoyX//6183bb78dMeatt94ykydPNomJiWbAgAHmBz/4gWlqaooY85e//MVcccUVxuVymUsuucQ8/vjjpzzWb37zG5ORkWFcLpe56qqrzMsvv9zhuVxIp1u36upqM378eNOvXz/jdrvN0KFDzfz58yOuA2NMz1u3cDhs7rjjDpORkWESEhLMJZdcYu68886Ij+5yXovU3pr11HNajDEnXcoPAADAArwHBgAAWIeAAQAA1iFgAACAdQgYAABgHQIGAABYh4ABAADWIWAAAIB1CBgAAGAdAgYAAFiHgAEAANYhYAAAgHUIGAAAYJ3/BxSXmUwn8rDYAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f58fe2d0-3c62-412f-8984-ff5d67ea9b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After above work, re-classification of contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 500\n",
      "working on HD 1000\n",
      "working on HD 1500\n",
      "working on HD 2000\n",
      "working on HD 2500\n",
      "working on HD 3000\n",
      "working on HD 3500\n",
      "working on HD 4000\n",
      "working on HD 4500\n",
      "working on HD 5000\n",
      "working on HD 5500\n",
      "working on HD 6000\n",
      "working on HD 6500\n",
      "working on HD 7000\n",
      "out of 7057 total HDs, there were 6909 52 15 81 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"After above work, re-classification of contiguity problems?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "1ef683a2-4429-4a91-b1ea-a9b0950dea22",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on current HD diam for HD number 0\n",
      "working on current HD diam for HD number 1000\n",
      "working on current HD diam for HD number 2000\n",
      "working on current HD diam for HD number 3000\n",
      "working on current HD diam for HD number 4002\n",
      "working on current HD diam for HD number 5002\n",
      "working on current HD diam for HD number 6002\n",
      "working on current HD diam for HD number 7002\n",
      "here is the histogram of HD diameter = sqrt(area)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDdiam = [0. for t in range(nHDs)]\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on current HD diam for HD number\",t)\n",
    "    HDdiam[t] = (HDpoly[t].intersection(MAP) ).area ** 0.5\n",
    "plt.hist([HDdiam[t] for t in popHDlist])\n",
    "print(\"here is the histogram of HD diameter = sqrt(area)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "45e3c17c-8c16-4bc5-b7fc-25b9250ed11a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we will regrow all disco'd HDs off by more than 36835 but less than 184178\n",
      "... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\n",
      "This is a total of 133 HDs to triage in this block\n",
      "working on swell-filling discontig HD 25 our 1 th HD we think we can swell out of 133 0.0 sec elapsed\n",
      "working on swell-filling discontig HD 1066 our 11 th HD we think we can swell out of 133 0.762 sec elapsed\n",
      "working on swell-filling discontig HD 2723 our 21 th HD we think we can swell out of 133 1407.684 sec elapsed\n",
      "working on swell-filling discontig HD 3898 our 31 th HD we think we can swell out of 133 1527.798 sec elapsed\n",
      "working on swell-filling discontig HD 4993 our 41 th HD we think we can swell out of 133 3496.834 sec elapsed\n",
      "working on swell-filling discontig HD 6137 our 51 th HD we think we can swell out of 133 9543.594 sec elapsed\n",
      "working on swell-filling discontig HD 998 our 61 th HD we think we can swell out of 133 10309.412 sec elapsed\n",
      "working on swell-filling discontig HD 1453 our 71 th HD we think we can swell out of 133 11325.7 sec elapsed\n",
      "working on swell-filling discontig HD 1958 our 81 th HD we think we can swell out of 133 11978.802 sec elapsed\n",
      "working on swell-filling discontig HD 3002 our 91 th HD we think we can swell out of 133 12758.932 sec elapsed\n",
      "working on swell-filling discontig HD 3433 our 101 th HD we think we can swell out of 133 13414.6 sec elapsed\n",
      "working on swell-filling discontig HD 4749 our 111 th HD we think we can swell out of 133 15714.195 sec elapsed\n",
      "working on swell-filling discontig HD 5792 our 121 th HD we think we can swell out of 133 18947.438 sec elapsed\n",
      "working on swell-filling discontig HD 6999 our 131 th HD we think we can swell out of 133 19667.848 sec elapsed\n",
      "we partially regrew 112 HDs, leaving 36 to regrow from scratch\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE CANSWELL CODE\n",
    "print(\"Here, we will regrow all disco'd HDs off by more than\",int(aDP-minPostFixPop),\"but less than\",int(0.25*aDP) )\n",
    "print(\"... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\")\n",
    "HDnAddedUnits = [0 for t in range(nHDs)]\n",
    "maxGap = 0.9 * np.median(unitPop)  #set a reasonable gap prior to picking the last block\n",
    "HDdiam = [HDpoly[t].area ** 0.5 for t in range(nHDs) ] #in case not defined before\n",
    "badDiscoList = list()\n",
    "nCanSwell = 0\n",
    "triageList = discontigOnly + bothProblems\n",
    "print(\"This is a total of\",len(triageList),\"HDs to triage in this block\")\n",
    "startTime = time.time()\n",
    " \n",
    "for i,t in enumerate(triageList): #canSwell\n",
    "    if i%10 == 0:\n",
    "        SEC = r3(time.time()-startTime)\n",
    "        print(\"working on swell-filling discontig HD\",t,\"our\",i+1,\"th HD we think we can swell out of\",len(triageList),SEC,\"sec elapsed\" )\n",
    "    distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    if contigPop < 0.50 * aDP or contigPop > 2.*aDP - minPostFixPop:  #formerly < 0.75 aDP\n",
    "        badDiscoList.append(t)\n",
    "    else: #rebuild from this big piece\n",
    "        nCanSwell +=1\n",
    "        gap = aDP - contigPop\n",
    "        origGap = gap\n",
    "        currList, addedList = contigUs.copy(), list()\n",
    "        adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "        nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "        nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "        stillGoing = True\n",
    "\n",
    "        while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "            while i < len(nearHDscore) and notYetPicked:        \n",
    "                listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "                if canAdd:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't add any more units without creating an enclave\n",
    "            else: #we selected the best unit to add legally\n",
    "                gap -= unitPop[unitNoToAdd]\n",
    "                addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "                currList.append( unitNoToAdd)\n",
    "                for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                    if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "                del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                for i, uu in enumerate(nearHDlist.copy()):\n",
    "                    if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                        del nearHDscore[nearHDlist.index(uu)]\n",
    "                        del nearHDlist[ nearHDlist.index(uu)]\n",
    "        for u in addedList:\n",
    "            unitUse[u] += HDweight[t] * nDistricts\n",
    "        for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "            unitUse[u] -= HDweight[t] * nDistricts       \n",
    "        HDunitList[t] = contigUs + addedList\n",
    "        HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "        HDnAddedUnits[t] = len(addedList)\n",
    "    \n",
    "badDiscoList += enclaveOnly\n",
    "print(\"we partially regrew\",nCanSwell,\"HDs, leaving\",len(badDiscoList),\"to regrow from scratch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42312f1e-ca1a-4b5f-8259-7d16e1c143e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#note for WI only - stopped/restarted after ~15 swells complete, as it appeared to be stalled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f57325dd-523c-466a-80cb-8e10b739b4ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous avg use and its sd are 1.01227 0.1214\n",
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01129 0.12152\n",
      "CCB cluster 0 = unit 6836 with pop 13737.0 now has use of 0.9979235518224625\n",
      "CCB cluster 1 = unit 6837 with pop 169151.0 now has use of 1.0075677187133645\n",
      "CCB cluster 2 = unit 6838 with pop 171003.0 now has use of 1.0040236061514873\n",
      "CCB cluster 3 = unit 6839 with pop 92501.0 now has use of 1.020536103016806\n",
      "CCB cluster 4 = unit 6840 with pop 51938.0 now has use of 1.021837828006021\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"previous avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "0ce918e1-0d30-4930-9fb8-0769d793683c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 1000 time is now 39\n",
      "working on HD 2000 time is now 84\n",
      "working on HD 3000 time is now 124\n",
      "working on HD 4002 time is now 159\n",
      "working on HD 5002 time is now 194\n",
      "working on HD 6002 time is now 228\n",
      "working on HD 7002 time is now 267\n",
      "out of 7057 total HDs, there were 7036.0 contiguous and 6988.0 complement-contiguous HDs\n",
      "11 HDs had both discontiguity problems, while enclave-only = 58 and discontig only= 10\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 21 58\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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jx3TDDTcoKCjIOb311lvau3evS99u3bo5/27ZsqUk6fDhw5Kk7OxsDRo0qNrrXbNmjQYNGqRWrVopODhYd955p44cOeL8SeWmm26Sj4+P/vGPf0iS/vu//1sOh0MJCQmSpG3btmnPnj0KDg521hwWFqbS0tIz6naH+Pj4M+ZP7/nYvXu3unfvriZNmjjbr7nmGlVWVrr8NNW9e3cFBga6jFFcXKzc3Fy312sTB5wCAGrk9HEJq1atUqtWrVza/Pz8XOZ9fHycf3t4eEg6dbyIJAUEBFR7nfv379ctt9yi8ePH6+mnn1ZYWJi+/PJLjR07VuXl5QoMDJSvr69uv/12LV68WKNGjdLixYs1cuRIeXt7O+vu1auX3nnnnTPGb968ebVrQe2x5wMAUCNdunSRn5+fDhw4oPbt27tM0dHVP1umW7duSk9Pr1bfrKwsVVZW6sUXX1S/fv3UsWNHHTx48Ix+SUlJWr16tXbu3Km1a9cqKSnJ2dazZ0999913atGixRl1h4SEVLvu6srIyDhjvnPnzpKkzp07a9u2bSopKXG2b9y4UZ6enurUqZNz2bZt23T8+HGXMYKCgmr0OtdHhA8AQI0EBwfrkUce0eTJk/Xmm29q7969+uabb/TKK6/ozTffrPY4KSkpWrJkiVJSUrR7925t375dzz77bJV927dvr4qKCr3yyiv6/vvv9fbbb+vVV189o9+AAQMUGRmppKQktW3bVnFxcc62pKQkNWvWTEOHDtUXX3yhffv2ad26dXrwwQf1448/nrXOPXv2KDs7W3l5eTp+/Liys7OVnZ193oNUly1bpjfeeEP/+te/lJKSoq+++sp5QGlSUpL8/f01ZswY7dixQ59//rkmTpyoO++8UxEREc4xysvLNXbsWO3atUsff/yxUlJSNGHCBHl6Nuyvb352AYD66pd/1dv1PPXUU2revLlSU1P1/fffKzQ0VD179tR//Md/VHuM66+/XsuWLdNTTz2lWbNmyeFwaMCAAVX27d69u2bPnq1nn31W06ZN04ABA5Samqq77rrLpZ+Hh4dGjx6t5557TtOnT3dpCwwM1IYNG/TYY49p+PDhOnr0qFq1aqVBgwbJ4XCctc57773X5SyeHj16SJL27dunyy677KyPmzlzppYuXaoHHnhALVu21JIlS9SlSxdnLZ9++qkeeugh9enTR4GBgRoxYoRmz57tMsagQYPUoUMHDRgwQGVlZRo9erRmzJhx1nU2FB7GGFPXRfxeUVGRQkJCVFhYeM43wwU5mC39/TrpvvWnzm2vbT8AqKXS0lLt27dPbdu2lb+//6mFXOG0wfPw8NDy5cs1bNiwCx7j7rvvVkFBgVasWOG2umqryvfr/6rJ9zd7PgCgvgmNPhUELvF7u6DxInwAQH0UGk0YQKNF+AAAwM3ccUTDokWLal9IPdWwD5cFAAANDuEDAABYRfgAgHqgnp14CFTJXe9TwgcA1KHTlx8/fX8SoD47fWE1Ly+vWo3DAacAUIe8vLwUGhrqvNlaYGCg8x4oQH1SWVmpn3/+WYGBgc775VwowgcA1LHIyEhJ/3e3V6C+8vT0VExMTK0DMuEDAOqYh4eHWrZsqRYtWqiioqKuywHOytfX1y33lSF8AEA94eXlVevf0oGGoEbxZcaMGfLw8HCZYmNjne2lpaVKTk5WeHi4goKCNGLECOXn57u9aAAA0HDVeN/JFVdcoUOHDjmnL7/80tk2efJkrVy5UsuWLdP69et18OBBDR8+3K0FAwCAhq3GP7t4e3s7D476vcLCQi1YsECLFy/WwIEDJUkLFy5U586dlZGRoX79+tW+WgAA0ODVeM/Hd999p6ioKLVr105JSUk6cOCAJCkrK0sVFRVKSEhw9o2NjVVMTIw2b97svooBAECDVqM9H3FxcVq0aJE6deqkQ4cOaebMmerfv7927NihvLw8+fr6KjQ01OUxERERysvLO+uYZWVlKisrc84XFRXV7BkAAIAGpUbhY8iQIc6/u3Xrpri4OLVp00bvvfeeAgICLqiA1NRUzZw584IeCwAAGp5anawbGhqqjh07as+ePYqMjFR5ebkKCgpc+uTn51d5jMhp06ZNU2FhoXPKzc2tTUkAAKCeq1X4KC4u1t69e9WyZUv16tVLPj4+Sk9Pd7bn5OTowIEDio+PP+sYfn5+cjgcLhMAAGi8avSzyyOPPKJbb71Vbdq00cGDB5WSkiIvLy+NHj1aISEhGjt2rKZMmaKwsDA5HA5NnDhR8fHxnOkCAACcahQ+fvzxR40ePVpHjhxR8+bNde211yojI0PNmzeXJM2ZM0eenp4aMWKEysrKlJiYqHnz5l2UwgEAQMNUo/CxdOnSc7b7+/srLS1NaWlptSoKAAA0XrW/OwwAAEANED4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGBVrcLHrFmz5OHhoUmTJjmXlZaWKjk5WeHh4QoKCtKIESOUn59f2zoBAEAjccHh4+uvv9Zrr72mbt26uSyfPHmyVq5cqWXLlmn9+vU6ePCghg8fXutCAQBA43BB4aO4uFhJSUl6/fXX1bRpU+fywsJCLViwQLNnz9bAgQPVq1cvLVy4UJs2bVJGRobbigYAAA3XBYWP5ORk3XzzzUpISHBZnpWVpYqKCpflsbGxiomJ0ebNm6scq6ysTEVFRS4TAABovLxr+oClS5fqm2++0ddff31GW15ennx9fRUaGuqyPCIiQnl5eVWOl5qaqpkzZ9a0DAAA0EDVaM9Hbm6uHnroIb3zzjvy9/d3SwHTpk1TYWGhc8rNzXXLuAAAoH6qUfjIysrS4cOH1bNnT3l7e8vb21vr16/X3Llz5e3trYiICJWXl6ugoMDlcfn5+YqMjKxyTD8/PzkcDpcJAAA0XjX62WXQoEHavn27y7J77rlHsbGxeuyxxxQdHS0fHx+lp6drxIgRkqScnBwdOHBA8fHx7qsaAAA0WDUKH8HBwbryyitdljVp0kTh4eHO5WPHjtWUKVMUFhYmh8OhiRMnKj4+Xv369XNf1QAAoMGq8QGn5zNnzhx5enpqxIgRKisrU2JioubNm+fu1QAAgAaq1uFj3bp1LvP+/v5KS0tTWlpabYcGAACNEPd2AQAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgVY3Cx/z589WtWzc5HA45HA7Fx8frk08+cbaXlpYqOTlZ4eHhCgoK0ogRI5Sfn+/2ogEAQMNVo/DRunVrzZo1S1lZWdqyZYsGDhyooUOHaufOnZKkyZMna+XKlVq2bJnWr1+vgwcPavjw4RelcAAA0DB516Tzrbfe6jL/9NNPa/78+crIyFDr1q21YMECLV68WAMHDpQkLVy4UJ07d1ZGRob69evnvqoBAECDdcHHfJw8eVJLly5VSUmJ4uPjlZWVpYqKCiUkJDj7xMbGKiYmRps3bz7rOGVlZSoqKnKZAABA41Xj8LF9+3YFBQXJz89P999/v5YvX64uXbooLy9Pvr6+Cg0NdekfERGhvLy8s46XmpqqkJAQ5xQdHV3jJwEAABqOGoePTp06KTs7W5mZmRo/frzGjBmjXbt2XXAB06ZNU2FhoXPKzc294LEAAED9V6NjPiTJ19dX7du3lyT16tVLX3/9tV5++WWNHDlS5eXlKigocNn7kZ+fr8jIyLOO5+fnJz8/v5pXDgAAGqRaX+ejsrJSZWVl6tWrl3x8fJSenu5sy8nJ0YEDBxQfH1/b1QAAgEaiRns+pk2bpiFDhigmJkZHjx7V4sWLtW7dOn366acKCQnR2LFjNWXKFIWFhcnhcGjixImKj4/nTBcAAOBUo/Bx+PBh3XXXXTp06JBCQkLUrVs3ffrpp7rhhhskSXPmzJGnp6dGjBihsrIyJSYmat68eRelcAAA0DDVKHwsWLDgnO3+/v5KS0tTWlparYoCAACNF/d2AQAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgVY3CR2pqqvr06aPg4GC1aNFCw4YNU05Ojkuf0tJSJScnKzw8XEFBQRoxYoTy8/PdWjQAAGi4ahQ+1q9fr+TkZGVkZOizzz5TRUWFbrzxRpWUlDj7TJ48WStXrtSyZcu0fv16HTx4UMOHD3d74QAAoGHyrknn1atXu8wvWrRILVq0UFZWlgYMGKDCwkItWLBAixcv1sCBAyVJCxcuVOfOnZWRkaF+/fq5r3IAANAg1eqYj8LCQklSWFiYJCkrK0sVFRVKSEhw9omNjVVMTIw2b95c5RhlZWUqKipymQAAQON1weGjsrJSkyZN0jXXXKMrr7xSkpSXlydfX1+Fhoa69I2IiFBeXl6V46SmpiokJMQ5RUdHX2hJAACgAbjg8JGcnKwdO3Zo6dKltSpg2rRpKiwsdE65ubm1Gg8AANRvNTrm47QJEyboo48+0oYNG9S6dWvn8sjISJWXl6ugoMBl70d+fr4iIyOrHMvPz09+fn4XUgYAAGiAarTnwxijCRMmaPny5Vq7dq3atm3r0t6rVy/5+PgoPT3duSwnJ0cHDhxQfHy8eyoGAAANWo32fCQnJ2vx4sX68MMPFRwc7DyOIyQkRAEBAQoJCdHYsWM1ZcoUhYWFyeFwaOLEiYqPj+dMFwAAIKmG4WP+/PmSpOuvv95l+cKFC3X33XdLkubMmSNPT0+NGDFCZWVlSkxM1Lx589xSLAAAaPhqFD6MMeft4+/vr7S0NKWlpV1wUQAAoPHi3i4AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCqxuFjw4YNuvXWWxUVFSUPDw+tWLHCpd0Yo+nTp6tly5YKCAhQQkKCvvvuO3fVCwAAGrgah4+SkhJ1795daWlpVbY/99xzmjt3rl599VVlZmaqSZMmSkxMVGlpaa2LBQAADZ93TR8wZMgQDRkypMo2Y4xeeukl/fWvf9XQoUMlSW+99ZYiIiK0YsUKjRo1qnbVAgCABs+tx3zs27dPeXl5SkhIcC4LCQlRXFycNm/e7M5VAQCABqrGez7OJS8vT5IUERHhsjwiIsLZ9v+VlZWprKzMOV9UVOTOkgAAQD1T52e7pKamKiQkxDlFR0fXdUkAAOAicmv4iIyMlCTl5+e7LM/Pz3e2/X/Tpk1TYWGhc8rNzXVnSQAAoJ5xa/ho27atIiMjlZ6e7lxWVFSkzMxMxcfHV/kYPz8/ORwOlwkAADReNT7mo7i4WHv27HHO79u3T9nZ2QoLC1NMTIwmTZqkv/3tb+rQoYPatm2rJ554QlFRURo2bJg76wYAAA1UjcPHli1b9Ic//ME5P2XKFEnSmDFjtGjRIj366KMqKSnRfffdp4KCAl177bVavXq1/P393Vc1AABosGocPq6//noZY87a7uHhoSeffFJPPvlkrQq7mPb8XKxSU3jWdv9fitW+Gv1sadrEV61CA+q6DAAA3MKtp9rWd4eLy9RC0kNLs7XzHKHiCo99WuV3/n62BPh4ac3D1xFAAACNwiUVPoqOV6iFpEdu7KTmHfuetZ//LyHScunlUVeptFlXewVWYc/hYk16N1u/lZQTPgAAjcIlFT5Oiw4LUPtWIWfv4BEkSWrfPEiKOkc/AABQY3V+kTEAAHBpIXwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAq77ouANWz53BxXZdQI02b+KpVaEBdlwEAqIcIH/Vc0ya+CvDx0qR3s+u6lBoJ8PHSmoevI4AAAM5A+KjnWoUGaM3D1+m3kvK6LqXa9hwu1qR3s/VbSTnhAwBwBsJHA9AqNIAvcQBAo8EBpwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACruMgY8L9+KjjeoK4kC7u4XxHOpiF+dtT1+5nwAejUh0fCi+t1vOJkXZeCeor7FaEqDfWzo67fz4QPQNJvJeU6XnFSL428Su1bBNV1OahnuF8RzqYhfnbUh/cz4QP4nfYtgnRlq5C6LgNAA8NnR81wwCkAALCK8AEAAKziZxfYU5ArHTtSvb6B4VJo9MWtBwBQJwgfsKMgV0rrK1Ucq15/n0Ap+SsCCAA0QoQP2HHsyKngMfx1qVnHc/f95V/SB+NOPYbwAQCNzkU75iMtLU2XXXaZ/P39FRcXp6+++upirQoNSbOOUtRV557OF04AAA3aRQkf7777rqZMmaKUlBR988036t69uxITE3X48OGLsToAANCAXJTwMXv2bI0bN0733HOPunTpoldffVWBgYF64403LsbqAABAA+L2Yz7Ky8uVlZWladOmOZd5enoqISFBmzdvPqN/WVmZysrKnPOFhYWSpKKiIneXpqPFJSoqM6f+Pdf4R4ulMiPtzz71N2qk4pcSdSzfpf1bK1Sx/9TV8/wKv1frMqO9+/JVVpR7zsf7HcnX5dXs6y7f/1yiyrJjKj5apKIiDyvrRMNRfLRIlWXH9O33h1R81P2fTWi4GuJnx+n3s7trPv29aow5f2fjZj/99JORZDZt2uSyfOrUqaZv375n9E9JSTGSmJiYmJiYmBrBlJube96sUOdnu0ybNk1TpkxxzldWVurXX39VeHi4PDzcmyKLiooUHR2t3NxcORwOt46NC8d2qZ/YLvUP26R+YrucYozR0aNHFRUVdd6+bg8fzZo1k5eXl/Lz812W5+fnKzIy8oz+fn5+8vPzc1kWGhrq7rJcOByOS/oNUl+xXeontkv9wzapn9guUkhISLX6uf2AU19fX/Xq1Uvp6enOZZWVlUpPT1d8fLy7VwcAABqYi/Kzy5QpUzRmzBj17t1bffv21UsvvaSSkhLdc889F2N1AACgAbko4WPkyJH6+eefNX36dOXl5emqq67S6tWrFRERcTFWV21+fn5KSUk542ce1C22S/3Edql/2Cb1E9ul5jyMqc45MQAAAO5x0S6vDgAAUBXCBwAAsIrwAQAArCJ8AAAAqy6Z8JGWlqbLLrtM/v7+iouL01dffVXXJTVYM2bMkIeHh8sUGxvrbC8tLVVycrLCw8MVFBSkESNGnHHRuQMHDujmm29WYGCgWrRooalTp+rEiRMufdatW6eePXvKz89P7du316JFi86o5VLerhs2bNCtt96qqKgoeXh4aMWKFS7txhhNnz5dLVu2VEBAgBISEvTdd9+59Pn111+VlJQkh8Oh0NBQjR07VsXFrvcz+vbbb9W/f3/5+/srOjpazz333Bm1LFu2TLGxsfL391fXrl318ccf17iWxuJ82+Xuu+8+4//P4MGDXfqwXdwrNTVVffr0UXBwsFq0aKFhw4YpJyfHpU99+tyqTi0Nnhtu51LvLV261Pj6+po33njD7Ny504wbN86Ehoaa/Pz8ui6tQUpJSTFXXHGFOXTokHP6+eefne3333+/iY6ONunp6WbLli2mX79+5uqrr3a2nzhxwlx55ZUmISHBbN261Xz88cemWbNmZtq0ac4+33//vQkMDDRTpkwxu3btMq+88orx8vIyq1evdva51Lfrxx9/bB5//HHzwQcfGElm+fLlLu2zZs0yISEhZsWKFWbbtm3mj3/8o2nbtq05fvy4s8/gwYNN9+7dTUZGhvniiy9M+/btzejRo53thYWFJiIiwiQlJZkdO3aYJUuWmICAAPPaa685+2zcuNF4eXmZ5557zuzatcv89a9/NT4+Pmb79u01qqWxON92GTNmjBk8eLDL/59ff/3VpQ/bxb0SExPNwoULzY4dO0x2dra56aabTExMjCkuLnb2qU+fW+erpTG4JMJH3759TXJysnP+5MmTJioqyqSmptZhVQ1XSkqK6d69e5VtBQUFxsfHxyxbtsy5bPfu3UaS2bx5szHm1Iezp6enycvLc/aZP3++cTgcpqyszBhjzKOPPmquuOIKl7FHjhxpEhMTnfNs1//z/7/kKisrTWRkpHn++eedywoKCoyfn59ZsmSJMcaYXbt2GUnm66+/dvb55JNPjIeHh/npp5+MMcbMmzfPNG3a1LldjDHmscceM506dXLO33HHHebmm292qScuLs785S9/qXYtjdXZwsfQoUPP+hi2y8V3+PBhI8msX7/eGFO/PreqU0tj0Oh/dikvL1dWVpYSEhKcyzw9PZWQkKDNmzfXYWUN23fffaeoqCi1a9dOSUlJOnDggCQpKytLFRUVLq93bGysYmJinK/35s2b1bVrV5eLziUmJqqoqEg7d+509vn9GKf7nB6D7Xpu+/btU15ensvrExISori4OJftEBoaqt69ezv7JCQkyNPTU5mZmc4+AwYMkK+vr7NPYmKicnJy9Ntvvzn7nGtbVaeWS826devUokULderUSePHj9eRI0ecbWyXi6+wsFCSFBYWJql+fW5Vp5bGoNGHj19++UUnT5484+qqERERysvLq6OqGra4uDgtWrRIq1ev1vz587Vv3z71799fR48eVV5ennx9fc+4OeDvX++8vLwqt8fptnP1KSoq0vHjx9mu53H6NTjX65OXl6cWLVq4tHt7eyssLMwt2+r37eer5VIyePBgvfXWW0pPT9ezzz6r9evXa8iQITp58qQktsvFVllZqUmTJumaa67RlVdeKUn16nOrOrU0Bhfl8upo3IYMGeL8u1u3boqLi1ObNm303nvvKSAgoA4rA+q/UaNGOf/u2rWrunXrpssvv1zr1q3ToEGD6rCyS0NycrJ27NihL7/8sq5LuaQ1+j0fzZo1k5eX1xlHCufn5ysyMrKOqmpcQkND1bFjR+3Zs0eRkZEqLy9XQUGBS5/fv96RkZFVbo/Tbefq43A4FBAQwHY9j9Ovwblen8jISB0+fNil/cSJE/r111/dsq1+336+Wi5l7dq1U7NmzbRnzx5JbJeLacKECfroo4/0+eefq3Xr1s7l9elzqzq1NAaNPnz4+vqqV69eSk9Pdy6rrKxUenq64uPj67CyxqO4uFh79+5Vy5Yt1atXL/n4+Li83jk5OTpw4IDz9Y6Pj9f27dtdPmA/++wzORwOdenSxdnn92Oc7nN6DLbrubVt21aRkZEur09RUZEyMzNdtkNBQYGysrKcfdauXavKykrFxcU5+2zYsEEVFRXOPp999pk6deqkpk2bOvuca1tVp5ZL2Y8//qgjR46oZcuWktguF4MxRhMmTNDy5cu1du1atW3b1qW9Pn1uVaeWRqGuj3i1YenSpcbPz88sWrTI7Nq1y9x3330mNDTU5ahlVN/DDz9s1q1bZ/bt22c2btxoEhISTLNmzczhw4eNMadOE4uJiTFr1641W7ZsMfHx8SY+Pt75+NOnrN14440mOzvbrF692jRv3rzKU9amTp1qdu/ebdLS0qo8Ze1S3q5Hjx41W7duNVu3bjWSzOzZs83WrVvNDz/8YIw5dRplaGio+fDDD823335rhg4dWuWptj169DCZmZnmyy+/NB06dHA5pbOgoMBERESYO++80+zYscMsXbrUBAYGnnFKp7e3t3nhhRfM7t27TUpKSpWndJ6vlsbiXNvl6NGj5pFHHjGbN282+/btM2vWrDE9e/Y0HTp0MKWlpc4x2C7uNX78eBMSEmLWrVvncorzsWPHnH3q0+fW+WppDC6J8GGMMa+88oqJiYkxvr6+pm/fviYjI6OuS2qwRo4caVq2bGl8fX1Nq1atzMiRI82ePXuc7cePHzcPPPCAadq0qQkMDDS33XabOXTokMsY+/fvN0OGDDEBAQGmWbNm5uGHHzYVFRUufT7//HNz1VVXGV9fX9OuXTuzcOHCM2q5lLfr559/biSdMY0ZM8YYc+pUyieeeMJEREQYPz8/M2jQIJOTk+MyxpEjR8zo0aNNUFCQcTgc5p577jFHjx516bNt2zZz7bXXGj8/P9OqVSsza9asM2p57733TMeOHY2vr6+54oorzKpVq1zaq1NLY3Gu7XLs2DFz4403mubNmxsfHx/Tpk0bM27cuDMCM9vFvaraHpJcPlPq0+dWdWpp6DyMMcb23hYAAHDpavTHfAAAgPqF8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMCq/wEbxI3lkTQEHAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "463db75a-694e-4c7d-9693-e10f3b4d65db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 699879 district pop vs 736714 target\n",
      "we'll also trim any HD with total islands' pop <= 14734\n",
      "working on HD 25\n",
      "Out of 21 discontig HDs 21 had discontig HDs.\n",
      "Of these, 11 won't be under 699879 after all minor discontigys were shed, while 10 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "There are 10 HDs still with both discontinuity problems\n",
      "Additionally, 3 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in sPgenerator:    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "39d37c15-759f-462c-b503-047b6b5e1554",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "52 81 10\n",
      "{5635, 2053, 1035, 1038, 1039, 4114, 1048, 25, 1049, 6172, 1056, 6176, 1058, 2082, 1061, 1066, 1078, 4668, 1086, 2627, 4680, 4700, 4732, 4744, 4749, 5774, 143, 5776, 5778, 5779, 5780, 5785, 5786, 5787, 5788, 5789, 5790, 160, 2721, 2722, 2723, 1698, 5792, 166, 5796, 5797, 1703, 6827, 6833, 1733, 1255, 3824, 1266, 1268, 765, 3841, 3844, 3848, 3855, 1807, 3352, 793, 794, 3866, 3358, 2849, 3875, 2340, 3369, 3883, 1324, 3375, 3381, 3897, 3898, 3903, 3399, 3411, 3412, 7002, 3420, 3428, 3433, 3434, 3435, 1395, 4991, 4992, 4993, 6027, 6033, 915, 2968, 6041, 6042, 1955, 2468, 1445, 1958, 2467, 6060, 1452, 1453, 1966, 440, 3002, 1472, 2503, 3532, 4565, 473, 989, 478, 992, 6115, 998, 1001, 4586, 4594, 5618, 1013, 5624, 6137}\n"
     ]
    }
   ],
   "source": [
    "print(len(discontigOnly),len(bothProblems), len(badDiscoList))\n",
    "print((set(discontigOnly).union(set(bothProblems)) ) .difference(set(badDiscoList)) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "2e54bac4-c327-473d-bbb4-257486bddd20",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 10\n",
      "swell-generating HD 1318 our 1 th HD we must regrow out of 10 0 sec elapsed\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[77], line 34\u001b[0m\n\u001b[0;32m     32\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[i]   \u001b[38;5;66;03m#nearHDscore.index(np.min(nearHDscore))\u001b[39;00m\n\u001b[0;32m     33\u001b[0m unitNoToAdd \u001b[38;5;241m=\u001b[39m nearHDlist[listNo]  \u001b[38;5;66;03m#add this unit ...\u001b[39;00m\n\u001b[1;32m---> 34\u001b[0m canAdd  \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43munitNoToAdd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcurrList\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     35\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m canAdd:\n\u001b[0;32m     36\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 809\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    807\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    808\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 809\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    811\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for iii,t in enumerate(badDiscoList):\n",
    "    if iii%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDunitList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "972705b3-fd86-4a26-ab4d-6bfc2bcb3c4a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1318 True True\n",
      "1946 True True\n",
      "1949 True True\n",
      "1956 False False\n",
      "1960 False False\n",
      "4702 False True\n",
      "6995 False False\n",
      "6999 False False\n",
      "7017 False False\n",
      "7018 False False\n"
     ]
    }
   ],
   "source": [
    "for i,t in enumerate(badDiscoList):\n",
    "    maxLOOP = 5\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    print(t,unbroken,noEnclave)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "02c40487-cf75-4156-b53f-cdef43b89892",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 10\n",
      "swell-generating HD 1956 our 1 th HD we must regrow out of 10 0 sec elapsed\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[81], line 34\u001b[0m\n\u001b[0;32m     32\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[i]   \u001b[38;5;66;03m#nearHDscore.index(np.min(nearHDscore))\u001b[39;00m\n\u001b[0;32m     33\u001b[0m unitNoToAdd \u001b[38;5;241m=\u001b[39m nearHDlist[listNo]  \u001b[38;5;66;03m#add this unit ...\u001b[39;00m\n\u001b[1;32m---> 34\u001b[0m canAdd  \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43munitNoToAdd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcurrList\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     35\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m canAdd:\n\u001b[0;32m     36\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 809\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    807\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    808\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 809\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    811\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "\n",
    "#restarting MUSTSPAWN code block for these WI hang-ups\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for iii,t in enumerate([1956,1960,4702,6995, 6999, 7017, 7018]): #(badDiscoList):\n",
    "    if iii%1 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDunitList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c15e9f0-0986-4dd9-8ab3-a52b6ba30bec",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #temp save for WI\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3mostlyContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5be77fe4-948d-41a5-80ae-14da9e58018d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c719d3de-2979-4613-a443-5ac20d75d831",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\n",
      "Must have already established unitGeoms, pops, topology in above blocks\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/WI7059opt3mostlyContigButOffPopUnit.csv ./2024state_HD_output/WI7059opt3AllBut7ContigButOffPopUnit.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999998588\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 7059 HD lists of units\n",
      "weighted unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 2\n",
      "working on avg unit-to-HDcp dist for HD 909\n",
      "working on avg unit-to-HDcp dist for HD 1751\n",
      "working on avg unit-to-HDcp dist for HD 2573\n",
      "working on avg unit-to-HDcp dist for HD 3418\n",
      "working on avg unit-to-HDcp dist for HD 4276\n",
      "working on avg unit-to-HDcp dist for HD 5092\n",
      "working on avg unit-to-HDcp dist for HD 5923\n",
      "working on avg unit-to-HDcp dist for HD 6762\n"
     ]
    }
   ],
   "source": [
    "#note for WI -- above seemed to stop.  Wrote to file, skip a bunch of above and restart from here 5-21 eve\n",
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\") \n",
    "print(\"Must have already established unitGeoms, pops, topology in above blocks\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3mostlyContigButOffPopUnit.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse,weights = unitPop)\n",
    "print(\"weighted unit use histogram\")\n",
    "plt.show()\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "cde04adf-178d-4383-a3f3-1f3e182f51c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current avg use and its sd are 1.01134 0.12148\n"
     ]
    }
   ],
   "source": [
    "#more WI special\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "42ddb4c6-a84a-45ec-be3e-bb9d1af51e20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 2 time is now 0 sec\n",
      "working on HD 534 time is now 8 sec\n",
      "working on HD 1127 time is now 17 sec\n",
      "working on HD 1645 time is now 29 sec\n",
      "working on HD 2164 time is now 41 sec\n",
      "working on HD 2676 time is now 51 sec\n",
      "working on HD 3210 time is now 60 sec\n",
      "working on HD 3746 time is now 69 sec\n",
      "working on HD 4276 time is now 79 sec\n",
      "working on HD 4786 time is now 87 sec\n",
      "working on HD 5302 time is now 98 sec\n",
      "working on HD 5814 time is now 105 sec\n",
      "working on HD 6338 time is now 114 sec\n",
      "working on HD 6879 time is now 125 sec\n",
      "out of 6678 total HDs, there were 6671 1 0 6 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 138 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "#more WI-special\n",
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "220b2fdf-a2a6-4b17-875d-20b6fd460b8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 773550 district pop vs 736714 target\n"
     ]
    }
   ],
   "source": [
    "#WI special if still enclaves -- rerun the CANFILL CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(enclaveOnly):  #internals + edgers):\n",
    "    if iii%40 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(enclaveOnly),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "95152535-877e-4d73-bf53-5a6f27b44367",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Of these, 0 wouldn't be over 773550 if all enclaves filled, while 0 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "49a35590-c4b4-4930-ab9a-cade750b93bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now overwrite these HDunitLists with the enclave fill\n"
     ]
    }
   ],
   "source": [
    "print(\"Now overwrite these HDunitLists with the enclave fill\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #temp save for WI\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3AllBut7ContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b30f5ed0-2781-4c1b-b310-64d4b21a04da",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "1492d71a-b4a8-4f5a-8c11-3fc17ce0d897",
   "metadata": {},
   "outputs": [],
   "source": [
    "maxGap = 0.9 * np.median(unitPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "90e69000-4506-4ea1-b50a-8ad836b62ed7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4702 587916.0853109744\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "badDiscoList = discontigOnly + bothProblems\n",
    "t = badDiscoList[0]\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "print(t, HDvPop[t])\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "87ed565e-b642-4d42-a2c8-424c71ae52fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, this HD didn't include its home unit. Add the home unit and southern border units\n",
      "4702 now has pop 696950.9653457934 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"OK, this HD didn't include its home unit. Add the home unit and southern border units\")\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({6840}))\n",
    "for u in range(nUnits):\n",
    "    if u not in HDunitList[t]:\n",
    "        if unitCP[u].x < -89 and unitCP[u].y < 42.8:\n",
    "            HDunitList[t].append(u)\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1fc7f4d3-2662-4fa7-8601-d03dba554e60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1956 now has pop 746045.3423139334 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[1]\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({2}))\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "afc285e2-95d6-479e-bf97-8425a6132ba2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1960 now has pop 745068.7404865819 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[2]\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({2}))\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "07e3ced4-4d37-4db9-8516-067584c9f2f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6995 now has pop 746712.5794373419 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[3]\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({2}))\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d6d967f4-d8a9-4431-a26a-af1167531737",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "what is wrong with HD 6999 ?\n",
      "6999 729278.1396088442\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linking bad HD 6999 along SW border\n",
      "fixed HD 6999 now has pop 750619.1396088442\n"
     ]
    },
    {
     "data": {
      "image/png": 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6l5Xx3fffsX3bdgBKlWJs1j30bTscALOiDAw3Zlk5ptuNiQ01KIjy9dkAOFIjGs3fk55OwebZuDbbUKxWFFvVX6sVNSgY0+3CtWcPqs2G4nTi6NoVo6SEig0b2X2wEpvp5Zz8FfwaMZAyfAvCdf1+Gy+un0p+oZvkgIanS/u7hDRpYRFCCHHqk4ClCQIDA7n2mmspKSlh87yviF31Ebr7HrL+swOb9RfcnnaYOA5L5QEsaEEGkZe3bTxzQ0cvKaH459W+YMfj8f11uzFdLtA0bG3bYupejNIy9Dxf64mtQweKQ88BNBJcucS6i3F68ykLDCbHEUJJvou4KCddBg1ruFhpYRFCCHEakYClGYKDgznn4ptg7BUYvzxL6fIcKr19CdBmYUuOQknuhWK3oeDBc7CEos3h6KU2Mp5aQWjXQwT/7tr6mVqtOHv0JOHpf9Q7ZbrdmKaJave1kpimSeWmzWihIdiSk9n7+DOs366TWLmfqzL2+9NVBJ3FzW98hcXa+C7MMuhWCCHE6UQClpawB6Fe9Awh4yoJ2TEDln0F6SsgYiKMeAUcITiAIMPEvXEzZXNWUbS1A/rrn+Do1xFbpw6oEZFVmTU+k0ex2eqcURQFZ8+afYwCHfVXzb345f/RKa6RAb61SMAihBDidCIBy7GwOqD7RN9j8zfw7R/gzfPgsregzQAUVcHeuwe2Ht2wvvsORbvaU7rfhcIqYn/fFkvH1KoBty0cdQsopsmfP/+RFTt2YAsIbFKwAmDovmBHuoSEEEKcDuRudbx0vxTuWADOcPjfGJj/HKbuWxNF0VSCf/97Eib3J/oKOyYBuDdurEpotjhcyc7Pw6yatjywc2f6tElsclpDWliEEEKcRhTTPOKk29NCcXExoaGhFBUVERLS0G7IJ5HugYUvkPmv1ynYGYgt1ERzKL7py4oKiorW/1+gWsCTD1oonr0L8ez7Cd8caCiwe5nXS2Ftqq0m33r/Siapm0IJLbVjddQe8Fu3e0lp8LCCaRh4XJVMuPdBUoc0PDD3RDEMF+Xl+xo4o/jXjVFqbXdQ+2/9TR4bO1/7r++511uEaXqx2aIOu4YGyj3sfFXdlDrnlKry6m7PULcONfVSFCuq2vi4IiGEONM05/4tXULHm2aFEZOxbfDCzk9wFykExMViDXWAaYChY+ZNwwwfALYgjNJcTO8BtPAwqm9uan4G7dIVcrrGVWWq1L0nVtnWtZiwQ27O0ROr4hmzfhdTnaem/5hh6HhclXjcruP/GRzF7t0vciDtfye93NamaQEMGbwQqzW8tasihBCnHQlYTpCI+x4j8OLrSbv197iLTeJe+g/29u0bufr2Oq9+uuJcQhX4130zjljGC9Mf5cPIb3nz5jeaXT9PZSWv/O4KLDbb0S8+zrzeElTVSb++H1UdMev8rQmsaqKt+sfMWmcaO1crrWlSVrYTXS8jJKR3nbONlVk3B/Ow/KuPHXbNYdf5yy7fxb59r+HxFEnAIoQQLSABywlkT0mh7aefcODWW9l37XUkvvgiQUOHHDWdqYB6sjrqWqlHMCioC6GhfU5qmZGR557U8morKFjOvn2vtVr5QghxupMRlyeYNTaWdh9/jLNXL9Juu430P/6RshUrONLQIVMB5UTHEcew6eLxcdoPnWqhM/V9CyHEsZGA5STQQkNJ+u/rxD3xBK49ezlw4+/Ye+lEin/6qcHrTeUUiCdOpEY2ZBRCCCEaIwHLSaJoGuHXXE37H74n+Z3/YYmLJePPf6Hg00/rX2uYGOrRb+rHZYJXa00SO/0npzWTBGlCCHEsJGA5yRRFIXDwYJL++1/Cb7iBzKf/RuX27XWuUXUTU2vaP41itvBG2KqtHHLzFkII0TwSsLQSRVGIvu9eME0qN22qc041DMwmtLAIIYQQZwoJWFpRxZo1ADh7965zXNFNDO3kBCyt1THT8vV9hRBCnIlkWnMrMkpLASj45FO0sFACBgwgcPBgX5fQCV4yX2nFbpnWLLvVVHXB/QYWlhZCiFYhAUsrCho9mtCJEylbsgS9rIzc/7xO8Nix6CXFpAWVcN3cKbx33gPYNAuzD27iuwO/8vvUCbR1hqAoCsWFuYCJt7IcUDAVwPDNMsI0q8a1mr6bpFmzgJppmugeD17NQpkJHsPEetK7oOTGLYQQoulkL6FThGmaFH7xBZmPPwHAV4MVPjtPQwvsx+JL3uKKWQ+RkTO7XroAw2D5/vRG8qxek1Xxv6bqtVdR6TtkOoVW3+elKeBQVRyqilNTcFY9d6gqDk3BoarYVQWbqmJRwKaoWFQFqwJWRUVVfP2LStV+OwpV2ycBKgpK9XkUcnNnkexZxW2DprboszIMg02bplFaur+BvYVqOcK5I7XyKMoRWrcU//9rVp66cYjy8q+JjHgNi6XNYeUdqS41exGlpKTgqLNvlBBCnN5kL6HTkKIohF91FZboaFw7dvLHSdfyzuwXCCz6mkGf9MdQAnAEdOPyztdQaXgxTYOQjZ8wMnMZGV3/6MujqtWiKjzx369rjlctHQ+4TYVCawjna8Vc2KkHFYZBpW5QaRhUGiYVuuE7Vut1sVfHY3rxGuAxTTymgccAj2lgVAVHBqY/MDKoDppM/3MDk3xPD5LUGG5r5meUkbGCjRtfQNfTcTizMIxGAocWNRY1HLcfz8lUXq+VH36Yj9fbsqDj/PPPZ8iQo6+ULIQQv0USsJxigkeMIHjECAB+Hf8I536zHVvlZhTTwx/73s9NHc/xX7ss7xC99i3CevUzzS6n0uOCxVu5xF7CFfERx63+TXH3ii9ZXRHcrDQHD65ly9brMcwgNEt7IiPupE+fG/3nD28oPOJKwi0415w0tV8ffm74eUqj546U56uvvorX6230eiGE+K2TgOUUFmO38d7Yt5m4ZjuPd0jguqRYZuYUsbvCxejIEEBt+RL+rdgTaJgKKkaz0mzf/j903cLw8+YSEBBW7/zh3SpH7Co6Df3W3o8QQjSXBCynA0Xj16IK3kjfQpbbi01R+Nvug9yQXcggdFj2GrjLoO1gSBwA1qZ0OVR1E7XCjdBE8XdTNYXbXYHLvQDd26/BYEUIIcRvnwQsp7hewU7OCw9mWWEpl8aGc0tiFB0C7PyUU8SysqrBm7OfBIsD5v0dNDt0HAWjnoCYVKgsgp2zIH8PBEZBeApoVjyuSiCKh8tjicgrJsFhI8Vpw3aCp1ODb2yL2oyAZcXKf2GxlJPa5a4TVykhhBCnNAlYTnGBmsZnfTrUO35pbDiXXngLjLwUrAGgWSFrM+xbDCvehNcHQ/dLfa9LsyAgEioKwdQB0FQ7nPsLJabGtRv2AOBQFc4ODeJ3iZGMiwpFPUGtL4ZpNmslFt1bhmmqJCeffULqI4QQ4tQnAcvpLqDWgNn4Xr7HWbfC8jdgzQe+bqLz/wZhSaB7oCgNDIMAzcJu1YErIIpSr06Gy8OGknK+zy7klk37GB4ezL+7JRNtsx73KpsozWphUTUbeEBRtONeFyGEEKcHCVh+iyx2GHKv71GbZoWI9v6XgVWPCKuFZKedQWFB3JEUw9y8Yv64ZRd9Fq8jXClBw0RVDN9fTDT/c9AUw3cMExTf1Onq1pP6f33nVnnb00VteO2YwxmGQUnxUkwzUgaeCiHEGUwCFlHPyMgQPu7k4e0tX2G1t8Vij0c3QTdNdBO8pul7Dr7jKBimUmeROqBm1Rez1nMUhtr2MjLC2aS6bNjwPnbHbiIiHj/O71IIIcTp5JgClmeffZbJkydz3333MXXq1DrnTNPkggsuYObMmUyfPp1LL7200Xxuuukm3n///TrHxo4dy8yZM4+leuIY9I49i0n7HsVuy6Bv3w9arTsmN3cNumGjR49rWqV8IYQQp4YWTwlZuXIlb7zxBr169Wrw/NSpU5vVhD9u3DgOHTrkf3z66actrZo4DhRFpUvnJykoXMHBg5+3Wj3at78Mi8XNxg0ft1odhBBCtL4WBSylpaVMmjSJt956i/Dw8Hrn161bx4svvsg777zT5DztdjtxcXH+R0P5ipMrImIIdnssla7MVquD3REDgGF4Wq0OQgghWl+LApZ77rmHCRMmMHr06HrnysvLue6663jttdeIi4trcp7z588nJiaGLl26cNddd5GXl9fotS6Xi+Li4joPcWKoqh1Dr2i18tetexldt9Ct2+WtVgchhBCtr9kBy7Rp01izZg1Tpkxp8Pz999/P4MGDueSSS5qc57hx4/jggw+YM2cOzz33HAsWLGD8+PHout7g9VOmTCE0NNT/SEpKau7bEE0UHNyNrOwf8XpLTnrZFRVFaNpirJYRBAREnfTyhRBCnDqaNeg2LS2N++67j1mzZjW4zf13333H3LlzWbt2bbMqcc01NQMqe/bsSa9evejQoQPz589n1KhR9a6fPHkyf/7zn/2vi4uLJWg5QTp2eJjlKy5gy9aH6NH9FVT15E0sW7X6X2iam9TUu09amUIIIU5NzWphWb16NdnZ2fTr1w+LxYLFYmHBggW88sorWCwWZs2axe7duwkLC/OfB7j88ssZPnx4k8tp3749UVFR7Nq1q8HzdrudkJCQOg9xYjidiXTv9gK5uXPYuvXBkzqWpKhwIR5PR+LjGx7YLYQQ4szRrJ/Lo0aNYuPGjXWO3XzzzaSmpvLQQw8RFRXFHXfcUed8z549eemll7jooouaXE56ejp5eXnEx8c3p3riBImOPp/u3V9i8+b7KSvfQ/duLxAY2PGElllalofDmUZQ4O9PaDlCCCFOD80KWIKDg+nRo0edY4GBgURGRvqPNzTQNjk5mZSUFP/r1NRUpkyZwsSJEyktLeWpp57i8ssvJy4ujt27d/Pggw/SsWNHxo4d25L3JE6A2JgLcDrasGnz/SxfcQFxcRNJafdHnM42J6Q8Q3ejKCaKGnhC8j8dmWbTtzMQQojfmhO/NW8Dtm/fTlFREQCaprFhwwYuvvhiOnfuzK233kr//v1ZtGgRdru9NaonGhES0ouzB/5Ex46Tycubz7JfR3Pw4JcnpKzVq1/BNBWSk4adkPyFEEKcXo55BOX8+fOPeL6hX4W1jzmdTn7++edjrYY4STTNTnLSzSQmXM2OnX9n67aHqHQdIqXdH47bXj/l5Xm4Pd+iMJj4+N7HJU8hhBCnN9lLSLSIpgWQ2uUZHI4E9uz5F7m5s2jb9k4iI4ZhsQQdU96rVv8DRfHSu/ejx6m2QgghTncSsIgWUxSFlHb3EBY6gD17X2bTpj+iKBpBQV0JCzuLsNCzCAvrj83W9DVUMg6uobLyBzyeYcTGdD6BtRdCCHE6kYBFHLPw8LPpH/4J5eX7KCj4lcKileTkzCIt7V0AAgLaExjYEaczGaezLU5nMkGBnbHZout1I61b9wiqGsCQwU+3xlsRQghxipKARRw3AQHtCAhoR2KibyHAyspDFBaupKhoDeXle8nJ/oVKVwam6VvB2G6LpUOHvxAfX7PsvqrmgNmLsLCEVnkPQgghTk0SsIgTxuGIJy7uYuLiLvYfMwwPlZXplJbtIDt7Jlu2PsiBtHcJCxtIaEh/NK0MjyerFWsthBDiVCQBizipVNVKQEAKAQEpxESPJTZmAjk5v5CbO5f09PfRNMjJ7sysWbMICAggNTWVyMjI1q62EEKIViYBi2hV0dGjiY727fpdUZHB6tUfUVLiIC9vKyUlJcyfP5/LL7+c1NTUVq5p61IURRaOE0Kc0SRgEacMpzORoUMfYuhQ32u328306dOZNm0a55xzDkOHDiUo6NimTAshhDg9ScAiTlk2m40rr7ySJUuWsGjRIlatWkXv3r1p164d7dq1Izg4uLWrKIQQ4iSRgEWc0lRV5dxzz2XAgAEsX76c9evXs3r1ahRFYdCgQZx77rk4nc7WruYJJ11CQogznQQs4rTgdDoZPnw4w4cPp7S0lFWrVrF48WJWrVpFcnIycXFx9O3bVwboCiHEb5QELOK0ExQUxPDhwxkwYAArV64kMzOTNWvWsHTpUsaOHcvZZ5/d2lU87qSFRQhxppOARZy2goKCGDFiBAAej4fZs2czY8YMFEVh4MCBrVy748s0zeO2uaQQQpyOJGARvwlWq5Vx48ahKAo//fQTqqoyYMCA1q7WcSMBixDiTCcBi/jNUBSFsWPHYhgGP/zwA1u2bGH48OEkJye3dtWOmQQsQogzndraFRDieFIUhfHjx3PllVdSVlbGO++8w/bt21u7WsfMNE1UVf5zFUKcueQbUPzmKIpC9+7dueOOO+jYsSM//fQTHo+ntat1TKSFRQhxppOARfxmqarKuHHjKCoqYuPGja1dnWMiAYsQ4kwnAYv4TYuKiiIpKYl169a1dlWOiWEYErAIIc5oErCI37Q9e/aQnp5+2g+8lRYWIcSZTgIW8Zv23XffkZyc7F+v5XTldrvJzs5u7WoIIUSrkYBF/KaZpkl5eTnbtm1D1/XWrs4xSU9Pb+0qCCFEq5GARfymXXbZZTgcDr744gteffVV0tLSWrtKLWKxWH5TC+EJIURzScAiftPatm3Lrbfeyp133onD4eDDDz88LVtaZPyKEOJMJwGLOCPExcUxYMAA3G53a1elxWTzQyHEmUwCFnHGiI2NBWD27NmtXJPmUzAx05bD7Kdgy3etXR0hhDjpJGARZ4w2bdowYsQIli1bRmFhYWtXp8ky1s7B7fGibZkOi/8Fn98Aure1qyWEECeVBCzijGO1WgkICGjtajSJt6KUt75dBEAMub6D130BmuxbKoQ4s0jAIs4oW7ZsITU1FZvN1tpVOarV3/yXZ557AQCn4iLlvOt9Jz65Ej66ohVrJoQQJ5/8TBNnFJfLdUoPXjW9HnRPJWu+eJGf9viOdQsq5qLbHgGHHWK7wYq3YNcs2L8M2g5q3QoLIcRJIgGLOKMMHTqUH374gaSkJM4+++zWrg7gm/2zZvqr/LLhIC7sdc5Nvv8P2EOjag50uwQ6jYX/nQ8fXQa/nw2x3U9yjYUQ4uSTLiFxRhkwYADnnHMOM2fOZP/+/a1dHQDmv/8Pvt+QVydYSQzw8NcH/1I3WKlmdcCkL8A0YO1HJ7GmQgjReqSFRZxxxowZw6ZNm9ixYwdt27Zt1bqkr5vLgn0eOgWUMHz0WGK6nI01MPToCYPjICwZcrad+EoKIcQpQFpYxBlHVVXi4uJYsWIFM2fOpKKiotXq8tV3MwCY+Lt7SOw3pmnBSrVBf4Ddc2HdpyeodkIIceqQgEWckS655BLOOuss1qxZw2uvvcamTZtaZTDu+QNTAfj87anNT9zvRkgeBBumHd9KCSHEKUgCFnFGCg4OZsyYMdxzzz20adOGL7/8kv/85z+sXbsWwzBOWj26jLgOCx6KPC3ond0xEzLWQGL/ZiUzTZPCrHIqyzzNL1MIIVqJjGERZ7TQ0FCuueYa9u3bx9KlS/n222/Zv38/l1xyyQnfcLBw7fd8/e13eEmka0Izfzt4KuGH+yGuBwx7sMnJ3JVeNi88yNKvdwFw4R97E9UmiMBQ+1FSCiFE65KARQigXbt2tGvXjvXr1zN9+nSioqIYOnToCS1z07dTOcC59LRnMGjC/zUz8VdQcggS+vlmDTXB1qUHWfXTPopzK/3Hfvj3etr1imLC3b2aV74QQpxkErAIUUvv3r3Jyclh9uzZ7N+/n1GjRhEXF3dCyup644vM+eBrNroS2fjWp3RhDx16DwR8Y2lUQFVAUUABVFVBwURVIO7Aj0QCK9vfRcWOHHR3JWZRJpFBNjRNq/ewWCzM/WAHADFtg7n4vj7oXpN5H22jOLeC7cszUVRQ8BWmKAqVZR6KcyvoMzqZgJBTf2VgIcRvm2Keyst+NlFxcTGhoaEUFRUREhLS2tURpznTNNm0aRNz586loKCAuLg4evToQY8ePQgLCzuuZVUUF5K5cS7vz9oAQBhFFBLC3XxADPmNptNNhRe9V/Ef/RIAemkH6WfNOGJZwYWpOI0Ibn9hFBabBsDSr3ex9pcDR0zXf1xbzrm0Q3PelhBCNElz7t8SsAjRCK/Xy86dO9m0aRPbt2/H6/XSt29fxowZg9PpPK5lfTB7HYsWziNRLfIfG3vFjfTt1AbDNNENEwMF0zTRDTBMMADDNDFM+N8XP1KRsZ2nH3kQwzDQdR2v14uu6/7Hj2+upiIf7nnpAn8Zpmmiew0woTC7gh9eXU9ZoYtOZ8WS0CmMyMQgYlNCUNUTO55HCHFmas79W7qEhGiExWKha9eudO3aFZfLxfr165k9ezY7duxg6NChxMfHExYWRkhICKp6bBPubhzdhxtH98Hr1Xn/+/nsWb+Mb378mUEP3dWk9EFOG5UYWK3WRq+x2a2UG3VnBimKgsWqsXtNNvM+2oYz2Makp84hLPb02M1aCHHmkIBFiCaw2+0MHDiQLl26MHv2bH7++ec659q3b8/48eOPuYXPYtG4deIophQU4zqwnu8WrubiYUeftmzRLKjmkadjq5paPTymDt1rMPvdLcR3DGXM73vgCGw86BFCiNYi67AI0QyhoaFcfvnl/PWvf+Wee+5h0qRJDBkyhPT0dN577z2Ki4uPSzn3XncBOiqL581u0vVWqxWLYh5xDRlVUzDN+l07qqpgdWjEpoRKsCKEOGVJwCJEC9hsNqKjo+nUqRPDhg3jlltuweVysXjx4uOSf6DDjke1E2AeeduAeWu28d+vZrNjj28jxwp344vBKSooDbSwKKpCULiDsiLXMdVZCCFOJAlYhDgOwsPD6dSpE3v37j1ueUYktgNg/vpdjV7z0w/fkblxMaHl6VRiRTvCWBpFVcBUKMwqpLKsss650oJKgiOatp6LEEK0BhnDIsRxEhUVxbp16/jyyy/p3LkzQUFBpKSktHjF3ItHDWHae1uZP/0jcnIncOWos+qcf//HRVgMD0psZx669So0VcFq0RrNz11RiqIH8vETazBNne5DbZx33bm89/m3VJSEEhJ1fGc+CSHE8SQtLEIcJ4MGDeKiiy5i//79fP3113zwwQd8/vnnLd4NOrVdGy646gYAVv+6qM65zLwi9q6cg8X0Eh0VhcNmOWKwUpSdxd7cVZQG7iAupQhF0dmyROedx76hYoFvh+j/bHq1RfUUQoiTQQIWIY4TTdPo378/999/P5MnT+aqq65i7969vPfee+i63qI8s/N9g3gDY9v6j+UXl/HB9/MA6D5kDHdfOeao+WRmpKE7FSqdB7jswUtJDZuNV6vAlR8GgFutZIltZovqKIQQJ4N0CQlxnKmqit1up1u3boSFhfHWW2/x66+/MmTIkGblY5omq2Z/C0B5UT6TX3wTU9exlGVjUUxcWElp07RtA8JjfNcFp+/lX9dcBEBplzAsnmAM1c2quMWsuH5Fs+onhBAnkwQsQpxACQkJDBw4kLlz5xISEkLPnj2bnPbBJ/5BYFUb6MZ8ABWbYtAhOAZrSCh/v+OaJi9YZ7P59gIqi4ojIK0EgICSeMpC0zB1G3369kFVGs+rODeHBR+9g+5xc9ZFl5OY2q3O+YrSEmwOB5pFpkULIU4MWZpfiBPM4/Hw3XffsWnTJjp06EDHjh0566yz0LTGx5zMWrWVOd9/RaVpYbHZBQMFjwElupUvb+nDgM6JTS6/3cM/AhCnFoNpEug28RDhPx+REEhQqN3/um/BHq7YMQ89K4uyzh2o6NWd5XNn4q4ei6Mo3PTCa0S2SQbg0M7tfPLoXxh4yRWce91NzfhkhBBnOlmaX4hTiNVqZeLEiYSHh7N7925+/vlntmzZwuDBg+ncuXODrSQ/z5mPVVF44J7bmRrjCy7mr9vBTdN2UlReWe/6xtT+PRIfFkBQUDBWxcnBnUUEhNgoL3YTHmAlIMAKJvy44SD3//gcheHhRA85h+l7N0LaDuI7dWHiw09itTt450+388mj/4c9MBB3eTmu8jIActP2H+MnJYQQjZOARYiTQFVVRo4cyciRI9m1axfz5s1j2rRpREdHc/HFF5OUlOS/9rn3phNUkYU7NInEmJqWkHaxEagY/PWr9TxcWsbEob2OWq5hGKCYaHYLWw07FBuglKHHWXjikq5c3yXef2122iFGz/+UAK8L/aFHSbhwFFx9IQDXPv1PlKrAatLf/8X6WTNwV5RhGAZrZ3wPgD0g8Lh8VkII0RCZJSTESdaxY0duu+02fv/732Oz2fjwww8pLCwEYMPeQ5TtXY8e0Y6/3jGpTrp28VG8flVXVFXl/h/SGPePb1i0ofFF5QB0XcfTJQxXtIP42EDiYgKJjw7EXeBi1s4c/3VlRaXknT+S1EU/sHPc1XS7YAQAkYqFdoGh/mAFIDAsnMFXXsfwG29j5E138KePp9Omaw9+A73LQohTmAQsQrSSNm3acMMNN2C32/n888/Jysril40HURUoK8xnW3p2vTRj+3Vk8eMX8+DQKA6VmdzwyTZ6//VrBj0+nZ9X76h3vWEYBCZ7ObdPCPNuHsT8WwYx75ZBqFYVt7tmqvWCy33rvRTbg7h46pP+bipVUTCPsD8RgGaxtnhxPCGEaKpjClieffZZFEXhT3/6U71zpmkyfvx4FEXhm2++OWI+pmny+OOPEx8fj9PpZPTo0ezcufNYqibEacHhcHDNNddQVlbG66+/TtDBlQCEGMVM//g9Vu7NJaOwglKXF6/uCxw0TeXuC8/m18cv5K4BoQxODkQ3Te75Yhv/+X5ZnTVf1q9/m1fMOxihLqhbsAJeo6ZFJDgvk/yQKIJfe8N/rLCwiCzVQpa7/h5DmxfM4ZNH/8KSLz7m/Qf+QNqWjeSlpx3Pj0YIIepo8RiWlStX8sYbb9CrV8P96FOnTm3yr67nn3+eV155hffff5+UlBQee+wxxo4dy5YtW3A4ZH8T8duWmJjIvffey8aNG0lLSyM0NJQ9B3NYmR/Ix28s919nURUSw520jQzkuoHJjO0ey0NXnAtAZn4x178+j+eX5PPhqi949Ow5OH7dBcMPYFUgJED1d9koioKiKOhVAcvmlZuIqihk/8Q7GTK0HwClBQWkrtvPDeHhxOUc5Km/P82jkx9FU1XyMtKY+Z+XAN8MIX/97DUzjYQQ4nhrUcBSWlrKpEmTeOutt3jmmWfqnV+3bh0vvvgiq1atIj4+voEcapimydSpU3n00Ue55JJLAPjggw+IjY3lm2++4ZprrmlJFYU4rWiaRp8+fejTp4//WLnbS1p+BYeKKiiq8FBc6eVAXhnr04u486PV9EwMZWLfROJDHRRWeJhy3VCufONXDrmCKZiSTeKfDlDdmROd9wodn2iHbvrWY8FjUP1zIu2r72kLKL8uAe4D4OofF0JiW8yqq4I2rGDVtm2c3a0bP7/+MgA3PPcKZQX5xHXswuy3XsVVUX7CPychxJmrRQHLPffcw4QJExg9enS9gKW8vJzrrruO1157jbi4o6/CuXfvXjIzMxk9erT/WGhoKGeffTbLli2TgEWcsQJsFrrEBdMlLrjOcdM0mb8jh0+XH2DKjK149LqDXVPz99HBlU55eN38zu3hRLfFYAIKcN85KQAMe+x+lsz6iei0HexdupqUwf0JqYpm9KoF5wDO6tKFopxsDu3cRkxKB2LatYd27X3XmQZe3aDMq2MAumliAIYJJiaaohBhlUmJQoiWa/Y3yLRp01izZg0rV65s8Pz999/P4MGD/a0lR5OZmQlAbGxsneOxsbH+c4dzuVy4XDX96sXFxU0qS4jfAkVRGNElhhFdYiiu9ODVTUKdVpbvyeH92S8yRF3HxOf+B8BU806i8c0GenZ0J+IiUurlFxDooN3/3qL4+mvY8+cHSPl1LvMSfHsX/XTeRG7/5F8AlHu9zHzN93zgJVf60y/bupXdK5aRFt+OPy3a2Gi9v+rTgSHhwY2eF0KII2lWwJKWlsZ9993HrFmzGhxb8t133zF37lzWrl173CrYkClTpvDUU0+d0DKEOB2EOGqWwh/cMYbBHZ+j3OvmwUVbiMnP5XHb87yo3UMg5bw341P+OOGPmPhaZEzT11pjGgbRiTHs7DGQlHWL+HbK6zDgbDCgyBlGVmQcsXmZ5BWXENehM+lbNxEWW9N6+ss3XxMEdLzgUv7brS2qoqACqgIqCpWGwZ1b9rMnL5/O3ppF7ywWC+Hh4ei6Tl5eXlWd6k+N1jSNyMhImYkkxBmuWUvzf/PNN0ycOLHOkuK6rqMoCqqqctddd/Haa6/VWblT13VUVeXcc89l/vz59fLcs2cPHTp0YO3atXX678877zz69OnDyy+/XC9NQy0sSUlJsjS/EFV0w2BHt+7NTudSLVx68bN1jgWFu7h5zTu+fC1WNK+HmHMH0WnYRWzfv5/cj3wzi2793zTCgoLq5Vnm1emwaCOjt6ykY05GnXO33nor27ZtY8mSJUes16RJk+jUqVOz348Q4tR2wpbmHzVqFBs31m3yvfnmm0lNTeWhhx4iKiqKO+64o875nj178tJLL3HRRRc1mGdKSgpxcXHMmTPHH7AUFxezfPly7rrrrgbT2O127DIjQYhGaaqK9a678bz+HwDKbhlMnn0AVmvdLhlFUaBq1hCKgttUYK/v3KWk8Q1JVJTYsAVfi6dsJqbpW4Z/y5YN7Fm9iaBy30aKqX96pMFgBXxruQB06NSJWy4aC/jGuk2bNo09e/ZQXFxMZGQkl156KQCeggxcP/0V1VOGVdFRveV4cweABCxCnNGaFbAEBwfTo0ePOscCAwOJjIz0H29ooG1ycjIpKTV956mpqUyZMoWJEyf613F55pln6NSpk39ac0JCgv8LTAjRfB3v+yOV48ey/5prSSiOp/+Tt6FY6v4nbxgGeev3oHu8KApE9erAO3NXc8fcLPZ5bATaPZR5rfzjwo5EmfdRZknn4tlPMKd/Z5yW23BpLt7oncw5qY3vQq1W9eQEBAWRnOzbMNHtdmOxWJg3bx4A8fHx/u0JMvfNpX3lagDytFgiyaJCzamfsRDijNIqw/a3b99OUVGR//WDDz5IWVkZt99+O4WFhQwdOpSZM2fKGixCHCNH585E/99fyHr6b5SvXkPFxD8SlRoPKKDAvvmbWZNR8yMj2TWbATcO4qXYQh46FIJXN8EC5/xaTGeLHbVdPO9e8j96FSoUWyArWOP+fRksO1LAUjU1unbfs81m4y9/+Qvvvvsu2dnZBAbW7EOkeH3dvZnXzSOufXd4JganXb4LhDjTNWsMy6mqOX1gQpyJKjZvJv3l//KLOrHB8+PGO5n1fQG6xcHcDh/xp8+XUaLE88jg2yhwhOAwTD4ygsm0GHRa8AJmRT5edxHvTbiCr0eNY8+4wY2WrZsmifPX8yeHwcOD+tU9p+tUVlbicDj8Y+PS3ryWwEPLCHtsD6rhhWei4dLXoc91x+8DEUKcEk7YGBYhxOnJ2b07nd78NwffWc2mFUWoKoyeEIbNphCcEE5E93booTt4/8f59E8fyx/uXk2P/BgeDvMSltSRj35YyBUBvpaSGQV7APAGWbnphy+5etYPfPPTcJKuupK+g89GVVWW7E9nSWYOhmFiYAIaDU3y0TTN37pSuPNXSjb8iP3gcsqC2hKhqmBWDeA//X9XCSGOkQQsQpxBzrulP52GFfLjaxtYt0Hn0r/0w2rztWx0Ht6ZDulbKV3iZFDmRWyMWsxbFZ/j3P4jbz7+CoNe8K299NSELjzx43bspR6MN98nY+4sIn+ZScAvM5gXn0jJ+Am8nNyJrbFtoKo7SDEN2gYHNlYtACqm30dS+Ta8aKTHXOA76I9yJGAR4kwnXUJCnIGy9hXz5bOrGHtbDzr2j/Efd1V6+O/bX6FuikSlZvkCt1bJ+Tf2wTt9J8vLyxmw4GkCXIUUDbyAcz54Ed3rZdWc+WR++TXJvy7C7Opmdup53P/Ef6vWTzGxqEfea/XglAF4bSEk/XlOzZorhgFPh8PFr0K/G07ERyGEaEXSJSSEOKLYdiEERzjYvSa7TsBid1i57w/X8PPiRWz9pBSrYSe6t5XctToL3t1GslNjZPoivkuNxCSCSXzCsvFbCL/1BoLc80gd4yB7hI47zkuvwuVYteogpeFF3/Zk7WHDrg3sObiHm11ZeI1CykqzCAquGggsLSxCiCoSsAhxhjrrwnbM/WAbni2fEBobiCUwwLc6rWoSqZic21PFWDuHoJe/xlBUygLiCS7LoFxToUcKCgoPp/blruSdZEQ85s/XUlC1+m5AKgCGafDPX/5J0aEigm3BULW/kMflwTxg4lE8VKhl6ECUJ4d1Gz+k7+AHfHlUBywtaAg2PToZjy3FmhREzN19ZKVcIU5zErAIcYZKPSee8rwy1n2Zy8EiMFUXhqJhKhqm6gs6Ri78GgDvpbdhbt9JUX4EuaEqUApA9H6diVd9xjM8QByHyCOKhPAMFEAxdQBK3CXkrswl0BtIsbVm3y9TMQkv7UhUaTu+7vkvRgSFAWGw8wPGf/AzF6T2Zvg51YvFmXg8HpYtW0aHDh1ISEgAaDQIce0pIufNDQB40kopX5VF4FlH34xVCHHqkjEsQpzhcl57jdx/v0rc008RMm4cKAomYBoKey+8AD0/n+DRo9GtLko7F2Pi4Oc5mVR38+xsl0q3EXv5n+33ZCnxACSV/0i+V6OzrSPnlGYyZNN3/OLpTbRSSHclnb25D9Spw9aYpSzo8Jn/dbe9wQzeFsp9qUsBKA2/gxcKAvznbZiE7N3PiB5XkNChi+9grW+y8vU5mG7d//rboSvJCi/076N0OLXcRsy2bnQN6+Z7V4pvnZrQKCf9xrZt2QcrhDgqGcMihGiyqDvvpHLjJjIff4Kir6cTP+Uf2KtWpnZ2707p/PkUzZ1J5ssef5pBXwWwLMx3I0+syOIf9sfq5JkWMAGAtcBaR0fU9gd4fq9vzyHd1PjvYXXYE7EegArPWFzlI1kRolDadQ/bvAOxemO4IicRLOv817tRcEa0JzQvlLK8TKwJgaDVDOpVAy3obp099nTeiv0KQ7VD1VqVymHjaUxM3JsCiNkzhNy2pf6z5SVuSvNd9D0/GUWV7iQhWpu0sAghME2TsqVLyXrm7+hFRaRMn441tmYw7vp5vyPXXOx/rZQoHDIT+Uto3c1JH3/rZbIio3jjskl1jmumTsbCkf7XPynDeKDyZsrM6j3BTGoPzG3jzKNMc9LGncs2dxI3x9m55/oBvPef/1Fg+LqjLnININYMBSD4jk6EptTv8nnm00dZWrGCn2755Yjv/91PvqVosY0//We8/9imhRks/HQ7d78+8ggphRDHQlpYhBDNoigKQUOG4PjkY/ZceBF5b75J3GOP+s/nfr0GJkJiyc3kpWdT2fVH4kgnyCyhVAlGzazAiHOyqUNnvJqFDkWH2B3q6x4albOT19YvZHb8DcT2v5CXt0cye1s2mqowKjWae0d2pEdCKKu355KdV8GI/vEEBtj8ZQ98+Cf0EiuhUeHc/fAfeeVvL9DGG4rd6wIN3P2UBoMVAAMdlSNPpwaoWB6I1VAxTdM/LsbQDVTL0dMKIU4OCViEEH6W8HCCzx9N6aJFdW7e1vUanolwwP4eVt/+hRSXRnDHsh+w6wGsT2nDj3H9WZ3aE7s9nJTKfB7ZWkavIgOIQ7MUU6G14aJvdSCbbvEhfHLb2YTVDky6xdSvEFVDUwxfQ7DVZucvf3ukye9HN3W0JgQsge1NSrfC/qwM2sW1AcDQTVRNuoKEOFVIwCKEqCNk7FgKp33G/vvvJ/CaaynLzSUkTycP0GwmRlWMUVIYQ5ndSX93Vy7dH88D6SUEFLtRHC4ULYzxXe+EBLgqvxuPFc1k3c4roSrtlkPFnPfPeb7xJIfFBLVfKgrkY5IfbqMlvGbTWlgmXD+Ajx9bwbfTF3HfXdcCErAIcaqR9k4hRB2BgwYR+/xzlP38C7k33UTF//0fFt2LfZOCVuAbc5KT3ZY9e84CICo5gAOpTubkechZPJXyBVMAuDH7IgCSvS6+TetKPioDEjKwqW4Aiiq8OG0aTquGw1L9ULFbVGwWFZumYlF9ez2rjSw8dzSGaaDVWrG3MVGR4Vj7FaNsiOSneQsB0L0GqiZfkUKcKqSFRQhRT8TFF7M4M5O9mzbhsVq5/IbrybnjNhaMv7DOdU5XMbPm/Rdb8DWolgT2tR1Ht+wl6IaHq3LP5/cX3UV4ahKv3DyWAXHreeneN1m3ZyWXvplNhKOYZZMnHLUuAybPIMZhbdH70NFRlaYFHTdffxEvpX3J3s8SeG7up4RawrEozhaVK4Q4/uTngxCiQRfffju3PfsslqQkflm+goPX153504Xd9M1fAECKupchdg95+gK+6hpP2+dH0va5EYSnJvkuViAouJvv2ljflOn8yhA27t9yQt+DYRpYmtDCAuB0OHjoiWuJu9SLBzflOV4OKQdOaP2EEE0nAYsQolEBAQFcftnlFO20YISs8h8fwRKu5AcGRGQQbS9l4VlOiqPmUBJgxVmayZdfzzgsJw1N8+3WHBoYxee3+gKZ5Ts3ndD66zRt0G01TdW4fNwYHv3b79Bu3s2SAR+fwNoJIZpDAhYhxBFFRcQSqoeSkPQrHTqs8B2jAAsGEfYKxqbuZ0cHB+v2rPenOfDF63hcLv/rqg2bScvL4/nvpnHnx5t9J9QAmqKlQ19102jSoNsG06KjqU1rnRFCnHgyhkUIcUTOIBttR/oWiEtI3E5C4nYyTZN8dwTlXidKgIe7jalsLE/1pzENg6LsTKKSapa1P1hYzIMvzcOtO+kWk8eF3eHCfmNOaN23mjspVyqafL1hGJimiWEYeNweMMGje/BNZvKFTf6/SsOvhRAnhqx0K4Q4qlUrbqGo1Dde5ZsdF9I+fDdF7lCCraUUFiSwsDiC7OAtOOy7uf4X30ItFoeBavFttOwpVwjrXUxs/1x2uRTezg6rylkFU/Ht4FzQE7JGVM0IMqs2UISsi3wbIIa7TczDYgKTmi2E/H+VmteVqsE1+yu5c1cFiukLLqr/D0A1FapDjoZaYhYHbOaJoPUoWgXWsNXN+swCKyxcviCxqozqyjXt6zYgNIzfv/o/rDb70S8W4jQmK90KIY6rvv3/w/wF3QG4pNMPPLnuCfJyAvm99hPXGv340EyAgsFYuj6MGXEVrsq5dDvLiVXTUBQVt7eQLbZEErSFtHd4GBJzEaYJBgamaZCWs4JDsYuIVjYw3rgTRdHANDFNeBGwGCY32XzdRzUtHfj/Vjdu1D4G8JxZzs5QC+l9S0FVUJSqTQAUBRSlplVEqX3Ml+FTS1zsKk+Cct94mxHtezC2a0cO/41XvaFi9XETk89XfsBW514GXXcjIQGNfQk33CKTvW8P63/5EU9lpQQsQtQiAYsQ4qg0zUHbtneyf/9/ySxKwGa185FtCv3VncCXXO6+k6+MYXT0duf9c/7J4EAPw71ODHclFjMIuy2SdgEO8hUPXi+8cdHkemVM++xJ/h7zFed2tHPOkCv9xz/8Zh6XVRbz0DWXNLveq35aj9vhYMSES5udNnPx93VePzPyDiIDg5uUdvOPM9gasZeuQ88jMjy2WeXuXLmM9b/82Kw0QpwJZNCtEKJJEuKvQFE0YkMyuUydwarkmjErcWohFnTW7rwBp26njc3AUm4n0NEe7BqlgemUeLdhOQQBGxr+2rn4gntxuGHJzlkYhsHOrUspKcw+WW+vnsfbVXKb5uWac708e01Uk4MVgIQuvs9Gs8hvQiGOF/mvSQjRJAEBKXTq+Bg7dj5J126LAPgpoQ0rV1yBaVG4XDnABE8PyHYyMH0nZq8/4Lz03jp5/DT5BkLnroWHGsg/OILepeF87VzG3H/350CYl0F54dD+KVo60M4odmOoLRsMG2EzGW9R6Dfh4man1VTfV6uB0aKyhRD1SQuLEKLJkpJuIDJyhP91p5x8nmAq1zGdMRykPRpdCy/HYYC57A0Aimu1kihWK5reePjx1MT/0NcVR2diUUyTHEslimm2OGA5JoqCcvgo3yanrfp7+s9pEOKUIS0sQohm6dTxYfLy5tE+5U+oe/4OQGf20Vl7jXTPSFz056fyvvycGMyOf/clPcRLRJlCL9pwbomFyCMELIntevDwlf/mpm+uw1QUuirx7IEWByxaiA21pYnr78vY9KRV2wG0KF6RIEeIBkkLixCiWbKyZ6BpQSQn347lgn9T7qj5GlEpB2CX40L08rb0MhJ5wHIBY+jOZiOdf/Tcw6w+sHT2BxhG/e6Swpx0/u+zm3Dh4amw63n0lg9aHDT4VK1Y15KUx9DCUj35yDRb3iUk67oIUZe0sAghmsw0TbKzfyQqaiSaZicx4Up4+EoWvDmAeMdBzMwMAvPDMTGJckXx2EMv+1eLvb+8mP9741K+ODebaRn/JOitfzI0P4rLzrqFCtPFOxveZnNYKUqIwpOxt3DxhfcDVSHHMbSStLR5pizvIFFmCoNf70uFXWdq3+c4r+/4JhbrCzZMQ1pLhDhepIVFCNFkFRX7KSvbSWxM3V2W9Y43kdbGSfqAF/jZ+SsFahkAhRWF/msCAkLoFZyKxVB4KelPXKz0ZVVYIbdnPM99B1+m3KJzl3MsP4z53B+sVDum234LEpd/+z39MvsS6Q2jJMCLVzN5c+PbTU5fvUO0YerNL1wI0SBpYRFCNJlXLwXAbq+7tsjIkX/gnXlLaWsu51BKFuf3n0hUaBSRgZF1rvMYbiwojB55K6NH3soDupeVK7/FU1nGkOuvQ9Ma+Eo6yWM6XG/dR/7uK+odHxY+rOmZVAcsDXR71WGaNf1HQogjkoBFCNFkh3IWsZkeFGXtwV7ga0VRFN9S9+mWJEo9ZYQMGM92h4Pt7lKW7F6NaZos3FJB31CFeaXlVFjbsGz+ahQUNFXBQnusFoV1yzahKtX5gaIqmCZE5eSx16kyb/deXyVM07eUvz+OqXpdveJs9TXAodJM2haWsHe+u94KtY0FQu6cJMor0ihy51Kg5xCXZ0czNNq0ieDHOR9iGLp/v6Hq56ZpVO1D5Pu7+8AGepQmsGjmz4Q4Q1EUUFUVUFBVhfWZFXy9H/IMJ3EU0zPEy9X9E0FRKMheTeygfAoKF1HuCa2qZ90NCPzzphp4D5oWQFjYQBkDI35zZC8hIUSTmKbJ+Hn/Y50yoEXprevz0TKbvhFhtZscK1tUXjWtpJCA9F3HlEdLlXTuAw21GlXJNgLZ5o1hmG2v/1jnLouJjd3baJqmGHjWDwQHdz2mPIQ4GWQvISHEcfdORi7rlAH8I1nn3IhIwMSo8+sf8t0udNVeZ6yrYZpctaWUAR2DuHOok8B9OQTHJ1e1TPgCIRPfAFVfbr7jhunbAHHmQvAGRNA5MZKgqGgsNhsRScn+lh2gav6xUqt3xfdkwScfYNgd3PDISzU7Lh+p5aF6hG9FDrO+/pJDe7ZzwT+eRlU1NEVD0VQ01bc/kqr6nqtVD/9zRWXjgvks//Adrrr8ctp16Ihh6BiGWfXXwDRMXnz9LWLUMmKqgpXE1P6MH9iN3fsdeM236NH9U0JD2xxWOerUX6kzh0qhrGwXa9fdgGG4mvrPKsRpQwIWIUSTvJ+RxyUxYdzSoV3zE29eS3xoKGMHdIFmNtB8tXgegeX57NmZDzt3AtCvUwcunnTDUdOutVkprlSJ6dWpmRXuSPCi+Rzas52uHfo1My3Y7U4AHE4nAcENL+l//sVXMG/pClA0NIuVC88/j/jIEHKKE8jPB6s1BocjoVnlejwFVc9O+4ZzIeqRgEUI0SQe0yDRbmtZYhO8zex99rjcXPjAR7QL1Qj0zYzm7E7RLN+eSXrmviaWa9LS5d8UteWTKKunMx9pHMmIfqmM6Jda73j1onMc07L+ErCI3x4JWIQQR+U1TDJdHmLtLfzKMH15NMf8b+axPSCW1N3b0RyHcJYXsmWrgdquK9klTQtCzGOYhXMsAYtRtWCc2oI8FKpnGDV/SrTh8ZVbuauQ0P7NTi7EKU0CFiHEUe0sr6TCMOkVHNCi9Ipp4mlGC4vX7eG9X9OII4DfV86l1GYh8sHJAOxN28CytV4WLHiP88676Sg5tbyl4Zhm2VQV25Kgp2ZZ/xYELKUeAIp/2YcxewWm28D0GFjjAoi+rSeKVWt2nkKcKmThOCHEUW0o8c3u6RHkrHcuz+XhpX2Z5Lg9R8yjsRYW3dB5YuaP7MzNBGDt7GVc9sAHLLHHk2pzoygqIZqdzv0upnO/ixlz8SNERFSwefPmo9b7WFpYqNrluSUTKatbWFoW9PijnRak9ZXn6B6Js3sUQUMScHQKw32ghMrdRS3IT4hTh7SwCCGO6vPMfAACtLo30TVFZVywxjcQ9n/puWwa2qPB9EojXUJ3ffM2M36NB+D9+Su5O7KM/+QFE6MFMqW7hSuvvYEv75vD7og2zHzxATRNQdMs5Of7AqdVq75iwIDLG6+4WTOCZf+2raya8zO6x0OHlB4Ubd7D2vUzUFC59sHniO9fdxqwv6XDMFC0+i0TXo8Hi9XacLFV71VtUdBRvcZK84Od6llDjk5hhHVt7z+e8cRSKjbm4kyNaEF9hDg1SMAihDiqNcW+TQ21w1oMvs8uIKown87795CQm83WMIWuPbrXS6/Q8KDbGb/G1Hql8p+8YG525jL5meuxWXxBQnFQLB7NTrs4B16vB6+3kqBgHUNXiIvreMR6F2YdwrA5eOm26zGKCzEVFcU0SVu2wH+NiYEtqH5X18GdvhaJFd/No+BQDoZhMvyGSwgMDWTlD/NZ+OELBIS1IyKxPUndezPospH+FhWj6r2qaguCjuOw3pt5WFdY6Lh2FH67G8WiENA/FmubIH799VciIw06dx4ii8yJ04IELEKIo3q8YwKP7Uwn1+0lylbztXHW/93HVdu3+F/rX3/MNwPORklsgzMyAnvHjvQYMQzFBM9hN9EuU28B6raOPNtV4aobbqgzWFVTLCS73Uya9I/mV7wqH0Wz0Ouya9mx3kp51o/0tfak1K5SWZFLRtEGwtom1ksaEpVM4cFVLJk2lepdFLct/hxncBsqivcD4Cp3c3D7GtI3z2X5V29jdUQQ3a4TRXl7fOUeQ5fQMS3peVixAX1iKPx2N2XLMylbnonWNohfsn4B4KKLZ9C/39+PoTAhTg4JWIQQRzU6MoTn9mj8/uuZ/DHYRojDTlBgAClVwcrWocOJv+4aitesRVu2jMBlSwguKiSoopxfzh+PcuH16Id1CSmulDqvw1ylLN9ZSf8t+1i0age9kiMYMHKg797bwru3JSoOl6uSe599B1VVWbHuJYzwCJa79+AJjyHc6wbA63WhHfZ1GJkYyYEN0Ov8m+l8Th8sNpVlX87k4I41xHUayVWP/QGr3Yppmiz7ciY7lq+gKPsAB7etwtALAfB4vc2uc/XsIE1ruLvpiGnLfeXpRXUXjlOdFhL/MRSAyu355E3b5g9qtm9bTf/mLzUD1IzvkRYacTLI0vxCiCZZt3s/9gnjGjyXunVLvZuWRzf45eKJmA4Hd9z1MIFuk2uiwgBfG4JuGExfvwevDme3j2DLznxy9LpBwy0hheRnHsCqurmqy0B0r2+lWEM30HXdt3KsbqDrBnrVKrLVe/zohkFGwWaCyGdM2AFQoKCg0F8+KIS7rJRUZBIaE1drnIrvfRRmZVPsUkhL/j+iznoao7IjmtEJDltd9nAKCuuXlFOZU4krtT2EHWUcy2FZRCr76NpuIcFZHbBio1R3kFUeQnC4FUv1tPJG4gO3Jx9b2Ap+2NcZxZKC1/TiRUc3vXhNHR0dLzqeSjelWgVmMNidDnRMvIaXsiIXI9Kvpm1pN9/Kw0bVSsSGiWFWrUZsVh2vFYBqFhXNqtJ7ZBsGXtS+4coJ0QBZml8Icdy1mfsLOUDYtGmU2BwUlZVRVFpGYudODf7CtmoqnuS22A/sR9cUip0Kb5YV172os28My2yAHjH18niDCEhpT7vcQ4Ssnw+AavqW5FcVFRUFlaq/StVzRfU9V1SCyaMru7BWFKFgEmsHw2tguiEIG/YAkwDVANehw1pyTJICKwkNKeVTd7qvXMcuvJVFmN6gmgoqZs3MaaXmBt7uLJ29+7tS4CnHLKj12dT6eag0EnVYdSsVgaFYzXRcKLgtThwRIXgAw6ugWg8LgGoNzjVVnfLszuyrVAkIyMGCBYvi21bArtqx4HtuCbZgDw3AHhWERbVgUS1oqsaH6z8ig31MGHa+b+sDtWozStW37YGi+jZvrH6uqAqmYaJ7TTYtzCAnrbTB9yTE8SABixCiSYq+/IrQSy4mvk9v4puYxiwqwl5Wil1ViLFa+L6Pb5Bs9S1WoWaQafUNXKm1J5DdovD7bzdQrkbz2COPoWhKsxZjq/z3rWiFpVgnr6lbL9P0B1mORtIe/PYdQtfezxV/upvtWzuTVfowpjuRISPeJCg08ojlzt3yL3qFvcZ1A34hNqRDk+sLsPKeGwh6v4K4774kvLNvAPOm//3MgpVWVMPDTc+chTOm4dk+2/fvZfaUvdx1g50xQ4Y0q1yAz9Z8hTVY5awJKUe/+DBpW/ObnUaI5pB1WIQQR6WXluHev79Za5KUV1SSumYF9vIyMAws6MQF2IkLsBNb9YgJsBPt9D2inDainDYinVYiHL5HoMWCw66Cw4KqKZRN+5qitz+n9Pu56AcPHrUOimoBs/44kqaMucjL8LUWKCj0GHglYZaH0QI3sXTZCHZs/PGIaU30qnKa/xVb3jUZAGtQzR5EPW4dy4QrwjFUKz8/PaPRtJaqbi1Db9my/qqiEp5Yf60dIU4F0sIihDgqxeYbAFr83ffEP/UUqtN3UzMrK9g1uDeK1UrKtz+hxbX1pwlwOth66ZV0/eYLAoqLsDncQK9ml20pSsPjiOfgX3/BJBaVYoxdVgqX7MbmXIRqq8TRLoDAC89HCQ4DwO0xmPnheg4uPUSZN5Hom0ZhouF0Wpn44mdYA4KOXChgVt30q1er7T/sNg7s7MP2vTeSlnMvzl2JJHXs03Ba00ABNLV5A2dN0yQvWCUasFjtdc61G92XDr9MY09hNKZhojQwZVqrWidHb2nAYmp4jeYPFBbiZJCARQhxVKrNRvL775N2113sn3Q9bf7zGta4OEzdwFuuAQY7ho/DFq6BomJUejB1k54WBS+QUppOlLVlGyc67ZkYqh17WB6W0CJCb5uIZ+U8ypftw/CqeMttFK6Po3D9RvYEqthVhcQSnX5AhhIEFJPYsSP792aSlq9TkZOBtW2Xo5YbmRgIedQJDJI7nYXN+Rmbd0xky/a7yEifwNnnPVKvxcYwdTR8U7KPpqCygGUHl/HL/l9YkL4AL17a3qLx9WExR1l6FvsKQ4mx5jcYrABYLL7yDL1lcyk0NPQW7GEkxMkgAYsQokkCzx5Iu08+Ju2uu9l52RVsPWcs0ZUHiQYiu5VgGopvUKjFRNVMFNXEXaZhC9aJshTiNmNbVK4tOAgMF1EPT6o5NmgstkE111TM+IH3djkotgSRbFXJTQ7EGmyjKP0cKjeuZtSjb3Bo7od88sZnfPX4PXTtlUpoXDwWmwPNYvE/7MFhRA26HEWzoFR3fx0WjMQm9mTP1j9Q4XyVMuNdVswPYsC596BZalpTTP/mh43v3aMbOlOWT+GzHZ/5j0U7o6G0jP2x5eS5CogttuKa8TpmWT6rV9vR1dFk6TEcXLyYhKFD6+WpVbUGtTToUFDRW7CHkd/pP+lUnMIkYBFCNJkjNZWULz5n/o13kzj7G6yqjj3cTXBXFznWSAxFRUfDQMVQVCwYeEwvXkUjW2/ZxokaoDc2j7eKc/yFXJy9j/6bC7nJvZlnx/qCm4XPzcDi9mIYBquLI7DZreiaytIVezHZ12Be1xoaCcOu8L82DytbURQGn38/abuHs2P/FZSa/2bOD5sZc+lb/msKKvOxehVUxcKevGwmvPYzbo+N350bxONjJuDW3Qz7bBhlnjIcmoMHz3qQ85LOIyYghl9m/Ju/ZL+J+91b0Mt24Azw7dHUKzweS4WXtWXjWDZ9N5c3ELD4W1iauTN2NRVVWljEKUsCFiFEs1iiohj67afc9dFqVu4rYOVfR+G0W0g+Qprt3y6looVj/DUFvE0YJJsY0452q37kPWd3HigpIDI4nJxdLjqXF/HStRf7r3O7IPC8K7n1d5fjrShB93jQPS6K923h89feZsH/XuGKGX8gwe7b8LGxtfIT2/Umbc8fqNBeRQuZy9a1P9C174UALMjcyOJ8J1OnX8gtnR6notw3q+edueA1fmRk90DKPGVEOaN4eODDjG031p+v1elb9M1SuQdvYAfMS6agJfcgMC+DwZ364vr7/8jNs9evEGA51jEsx9rCIsQJJAGLEKLZHFaNq89KYt72HCq8Bs6G759+gflpZCek+LoMFIWd6dt5avNm9hPAXZEWogMC6RadyMaMXdgsVs7rOghN8309mYqK2oSuhm/XzGKfM5Fu7kNEBPUGoKc6ECMwGt21CtPUMfRMFEzKFnwJt1+PM7BmJk5Im44E/+89CiqcuKydKavIR7cohHpNaOD9LZv9IpXW/6KXp2JX+5PU4Wz/uQFxZ7E4/3sKXcW8uPEBAjsGoVekYAnaxlcZdr7OLEFR4IlBTzA8aXidfLVg34Bg2z3f4WwzsOZ4RAymaaJqKl6j4a4mi1Y9hqWlAYuGQcvSCnGiScAihGiRUpfvl7jj8IXMGhDoLsNjszFi5k8UKXYO2qMIVmMpsQTy5xKgBMjKB3wtEUkZ85nepz2J0SnkGDZK9Uo+nfMA7UJT6N9jEjZHaL0ydhUVAdFsscXTffYiHrZn4g6MwV7eHs3WHrurAOfBf5MZ5gsI1v5zCgd2biM0KprUcRfSZvhIEiITObBvN0FPL2Tt6zNYut7O7Q3ESqXFOZQZH6MXdWX8xB/qnVerWmWmTfiEu36cQoF1I6p1AwBWI4azEnoSHxjH0IT63TpUjX/hsPEvBxcvYfpHLqAtEY7MBj9nu8U3sFnXW9ZKoqL6twYQ4lQjAYsQotlKXV7eXrSHHokhBNiO/jUSV+Hb7bmnUkKC3UWnEBiXOgCn1Y6rLI9f924kw+VhZIderNy8hHstHRmwpZiAyrWUO1KwGNt5Pm0G3nSF4A2vkWDC4KAU/nx1TbAwqec5hG5dgal7WGtqPKh35uLIHfQuj2Jv6CKGrl5FRmwQAZEVlGc5WbRuOQEmHCwuYMMbU7G8/hJeVSHcv4ePgl0BT7ELw7T6VndVFFBg5bynUW0mqV2fwltZUTVLqCayKSwtQTUV2gamMOPqtyhzu/g1fQfnJnfFZqn5vFweFy6Pq84sI5fH91mZHi9G1Ro2mCauwhLARrTjAAMndKIoraRq+fyq5fJ1MA1fsJNXks62rMUYpuFfO8fE8O/iXD0o2DTNmmOY5FoOYSuNYdHqg+i6ibcqb1030Q0Dw/DtRK3rpu+v4XsYhsn+4n10js0gO6fhYIp6gV/NgfL1OTjLOhCc0tHXBVfrs0ZRsEQ7sYQ7fMc1WT7sTCV7CQkhmu3hrzYwbWUaP/9pGF3igo96/eMvv8Fnh2JoZy3ENMFAwQBGxbt55J7b/dfpbg+lf+vFoWAbn6a+QGVoW7bvmU268i2/Xvslu/cvYMGen5ibvoACFX6+ZXOjZa7ftZpZ/57K5z12U2ErAaCtEsK9sVkU7wtmcK+XSRg0DG9lBbumfcLW99/B4fEy9K13Ce7ajb1Pzcda0fgsn6PJsuRxU6fHWpx+4f50wo2a7hnDVHk3+x0qzfqtS4eb2+EjdsSsbFG57cxoNm77S7PT3dnrHc6KW9eiMgGCDw0kYePdR70u/tGz0YJaNkVenHpkLyEhxAk1bWUaQJOCFYCrzuuLsnAtiqKgKr4uk6VZKosyD/8K0gnVDuIp68xTF58PwCOHviSzrBSLPZgunS+kc8cLWPDRIOwe30q03tIM3MW7q9b7VwAFd6WFtkRzJQbvoqECpqmyK+MitDZvEd6pmIJ77qDEEoJRUQFeL6lVv900j2/htIBYA88+jcqe4eCoGsRimpiGjq5tJyhCq7UfUN0NETM3FhB7MJk72tzR6JopjancvpGkoiXo8X/GFRdX1eLge1xcUU6B1hFsQTX7+VTt9YMCqAp7f15NWISL2EF/xqLZfFsdVNdRUao+IaWqVaf6FaAoLFrzL/DE8uCVfVFVBa1q7yBVVbCoKqqK77imoKkqWtVzVVGYs+pdDlb05pox/6v6qMwGVhRueOPINT/fghICCU8NrpkabZi4DpSQ917doNRzsAytswQsZyIJWIQQzRYf6uBQUSWZheVEmS4s4eFHvL5Tl16kzNpGREQIA0YMIKF9G57895ssy667Eqxmc1BpBBGl7sBTWoQ1KNR3X6u1wd+/v7mGDWY5WFSuerc3ZVYPl0V6SFKtFOwcRWV+CqUH+wD7gVu5ZOUhUoeF8NQmk6tTp/vzsXfqjHGwAGtoKJbYWIJHjSLsyivQgnxjXCxB4AGSR8Vhi4s67B11PeL7LSleBQcruH3QbdgCjjIi+TC7nVv5cGYcQ879HVGpdedeRVc9jkSds4VwJYxtB17hutFrm1X2ns3v4LXbObd/QpPTpO3aSNaWJbTNyyA/NAar9cj/W2iIig1UBdVe06JVsSWPvA+2+F/bkoOxdwjD3jGs2fmL3wYJWIQQzfbtPUMY9/IibnnmK7ZYImhfksnd5yQSFh7EeaPPwuqw46qo5IvP5/PF2oPs1EIpt0ZCHmjb13Cu+QvztUSClQrYNgMUFVSFfRuyScTDPvvFRGZn4y4swOOqqLOzcaWnDIA+hoVoawiz9HwyCtvg+fVudFcIqF7CktfTrVNbslaUQkkbRoTbOa/TLvT1W9mbDM4NCQT84WlUTUVRNRSLhi023B+sAChaVZktmHGjWHzjLLxuT7MDFqvd6k/bEiYGiqli0pLuLLVZ+0UBJH00lKSq5/uDS1pQJvii0rqfc/7nO/zPwy/vROBZcS3MW/xWHFPA8uyzzzJ58mTuu+8+pk6dCsAdd9zB7NmzOXjwIEFBQQwePJjnnnuO1NTURvO56aabeP/99+scGzt2LDNnzjyW6gkhTpCYEAeTzk7m33PdAOwJjuP/NutAEcHzvuc8WwnLKh3k2UMYaOpcGFJBahsH548dyPSvFjBjjwJO6KXshmn/8OfbDqgghNkHrsT1vK/bKTOpDLVWs8KDV//Ig7XqMvijnljSeqG7Quh3USX9Rg3H7hgDwOqcGezeAN997wKSgH/A5750a7fl1XlPqrGPW/85BFtoVdBS1ZVjepq/t45aFbAY3uYHO5bqgMXlbnZaAEU1sQV0Z8LgR5qfVqkZkNskes1nk+9Jwp3d9ggXH7Fk/+DfahFXdCLvo60A2NrJ2ERxDAHLypUreeONN+jVq+5mZv3792fSpEkkJyeTn5/Pk08+yZgxY9i7dy+a1njEP27cON59913/a7u9eb9KhBAn1z0jOuLyGry5cA8Az7V3s2BPAT9ZY1lb6WJUqIdJ49vS++wJddLde98V3Atk3jkB755N8PeXqqbymmRleKm0JzE+MATdq2N4dP6bNQuAzVu/Rjd1DEPHMHX06r8mKFVfZWu+t3H2+JrxDX3uGEvChgPobg/ohm8Wja5j6AamoYNhYnp10lbuY+OhSNylFf6ARan6vjKb2cLimfshcSvfQ7FE8fq/e3LzH68jKqp9k9Nb7b76e1wta2FBMQmyRRMW0JIWCbV5y+trFtaHjqJ30RwirGmUO1o2SFlBwTyshcXZI4rou3qT8/p6ShdmEH55pxblLX47WhSwlJaWMmnSJN566y2eeeaZOuduv71mxH+7du145pln6N27N/v27aNDhw6N5mm324mLkyY/IU4XDqvGXy/oSnmlh49WpFFW4eYff5nILZt302/YeFT1yNNPFVRcJUFw1i3+Yw3tNtT70yjWu3O5ZsUTjeZlUXy/9DV7BUqtrhBNU4nv2+6o76U8rwQOHRacqFVTlT1NX5fE2D4X68I/YAWwgM1MYNbsj7j2msebnIfVUdXC4mlpwKKjmM0b6Fsrcb2WjqPpcueHLHj3Qc7L/ojCKIU2LSpXrRewANjbhmDvHI5e0rLWJvHb0qKA5Z577mHChAmMHj26XsBSW1lZGe+++y4pKSkkJSU1eh3A/PnziYmJITw8nJEjR/LMM88QGRnZ4LUulwuXy+V/XVxc3JK3IYQ4DkrzCuhUkEaUNxdzgUYH3aDw812+9UOqHqZhVj3XMXXf2iAV+/Iwm7Cr8DuXfcfOvbNQUVFVC5qqoapWNNWCqmqs2fg7SjKD8UblcO2j45o9KwcgS1EBg59XbyJw7x5QFOw5uXQmkvW7izHLMvzXKlVxWO1xNdXPInftp3Zbit0MoHOn7s2qi7+Fxd38rigAUzGhhXsJVY1wblYKhzOQ8+5+jQ9+zMY0FXq0pNQjbL1gSwqmZF4antwKrFHOFuQufiuaHbBMmzaNNWvWsHJl43P8//Of//Dggw9SVlZGly5dmDVrFjZb49PQxo0bx2WXXUZKSgq7d+/mr3/9K+PHj2fZsmUNdiNNmTKFp556qrlVF0KcAIPWzeaOBV8CkFl/0dcjUprwDWSzB9M99bJGz+/eZCV977kAWCxBuCvLyU4/QGhEAkHhwUe8GVZbZA8gilIetodTavgiko7xSUzbW07iokKgsAnvBiCFCmt/FHTK9DG0HTea/v3PPnqyWqxO33el193yVgWzhQGLiYrSzICldtrDB842Xf1Bt9UCekVRMucAen6lBCxnuGYFLGlpadx3333MmjULh8PR6HWTJk3i/PPP59ChQ7zwwgtcddVVLFmypNE011xzjf95z5496dWrFx06dGD+/PmMGjWq3vWTJ0/mz3/+s/91cXHxUVtwhBAnxthLz+PQnC+JffQRLDExoKooqgqaBoqKotV6XetcwXN/oXLPoWMuX1FrumzefeQrdJcDb2UQcJCAqEP87ulrj9o91atNPAfZyZvxobSPqPlxZfS0oDqDDmt0qOo0MX3Pqp9X/8liOrvzC7kvPY8nooJoLktVC4u3BYN9AVDM5g2crcW31VPLAhZf20xLW3bUxtNWBZyKTVa4PdM1K2BZvXo12dnZ9OvXz39M13UWLlzIq6++isvlQtM0QkNDCQ0NpVOnTpxzzjmEh4czffp0rr322iaV0759e6Kioti1a1eDAYvdbpdBuUKcIry7d6M4nYRNnIgaGNjkdCUh9rrriLWQophMuPpNPBF/YN2cSkwq6DTAwtJPHNgD3UcNVgAcVbN64qOjaNfm6CvJHo0eALm5BZS1oJVEtaiopoKnxWNYWt4l5GthaRlfC4svyNp7901ULl+LOr4Lis1Gu/texBba0AglH0VRavZQOjxfj+949VRxceZqVsAyatQoNm7cWOfYzTffTGpqKg899FCD3Tem6duLovaYk6NJT08nLy+P+Pj45lRPCHGSGWVlFH7xBcGjRjUrWAHg0AbQj98Pj069h9Kx1xAy9qxi46KtQBsGTujTpLRa1Zor3iaMqWmK4KpWkp37f2ZpxU9VM2+q2mOqntdXteqsohAdv4OynW3I+3QbVU05VQ+zbnLTrPsc0CqCqMxew95512Is2gIOUPt1RtHqf90f3qqRoOyisqwNP/x3de2LqoIYk+rGF6XeOYgNCiWmNJG9H31K5dzlAHh/3IhaATvzJ2PrfbZv3I+iVb1PFQUVFBVbcScqHQHMmrKibheeCXqlF71cJ3BuOopdq/fR/ZJbxMIwk6ED6y92F7i+kLA52XQ7N8G3IaUCFquK121gsamoFpWO/WOITmrais2idTUrYAkODqZHj7pDqgIDA4mMjKRHjx7s2bOHzz77jDFjxhAdHU16ejrPPvssTqeTCy64wJ8mNTWVKVOmMHHiREpLS3nqqae4/PLLiYuLY/fu3Tz44IN07NiRsWPHHp93KYQ47rx5eeyfdD3eggKi7jn6HjD1WI5PsOKxQrGRy7wvP2f3SgVXUSTQhpjOh+jQc0ST8tDU6oClpWMw6gq0+Wb6OII3UFGxGKg9W1hp4LVZ1fPh+9u5M2hEUrG+c7PLVrCDO5islSsI/aSqe+mHDZRd5MXdq7E0PlbFSVRhJyz7y+oMvzWqLqoTKx32PDRgGLbyOPSCQrTYHuhZm3C2PRvXtuUE5PVCyUzwXenfjLG6H80kuLw/itaZPUXlDc6qVp0Wivc3vChdWE4Zg4M1fu1cWu9c773FhAFp2wqwOzRy0+pfU17kYtTvujX8wYhTynFd6dbhcLBo0SKmTp1KQUEBsbGxDBs2jKVLlxITE+O/bvv27RQVFQGgaRobNmzg/fffp7CwkISEBMaMGcPf/vY36fYR4hS279rr8Bw4QPsff8CektL8DGK6Qsae41KXHbuTyVoTRUyXA3S+MJLO/QbiDGz6+JGagOX4tLBY8XXnWAK6MOqc949ydX3zf+5NfOcE2tx5brPT7hg4DEdyAlH7bVjbBRD9wOPkvjQFyzuFhA1IIPKRF7Cl9mswbe4/PgAgasqwZpd7aMpyDIdB8qMjyQmroODTYrx52VjiuxBz/zgC+zW+eOjSPy8gUI3k+pfPa3a5U/69iqCcSuYOrJ//9Mr9HNyzm/Pu70XbiEBeu3Nu/QxO++1/zxzHHLDMnz/f/zwhIYGffvrpqGlqL/3sdDr5+eefj7UaQoiTLOSC8eT99w0qt2zB3qEDXl1nzsef0+mcs2jfuWMTcjgOA1gAmwcU3Teg3x6o0fvckc3OQ9WqVqY9TpvXa1V9Jw5H8lGubIQJlTsL2LBgMaUBGn3uH0iArWmLsunFOZRtygEg8qphBIy6hKTzLiDv0Zsp+GUVJddMIubGCwi99zkUy+G3gOZPa/ZXuVay6D9MIvoPk5qcNiTSgVre0kHGhxVei7+rz+s7H9M2mOz9JcSmhKBqCnkZZS0rU7QK2UtICNEi0ffdh/fQIQ5O/itpbh3tkckkAy7grauv56bJ/4fVcYRW0qoukOOhb5ccdgYfYtfieMpLSwgIat6YBKt2fLuEVNU3/dZqO3zTxKPzGibVgUNRqJWUbDcLp21i3I29m1Z2WDxG4SGCuwQTcv29ACgWK1HPfkT4nRvZd/WVHHrzJxyDxmI/53zyt/5KRd4hAiJiKSrPx2lv/symY6UoCk2Yfd5sWlUgWv3veuXks+qc//qF1c1a2Fe0LglYhBAtoigK8X//O3ppGaWPTK5zbuhnH5F76++ITz7SuqfH5w7la8wwaNM5gV2LTQ5s20bqgLOOlqyO490lVDNwtPn5KQqUWBQ2dwvitrMH8OvUlfTYUsz6JxeTeU4MY8cdeVyLYrXjHDiONh+8VO+c1q4nQb3aUrTyAOVBAXz/h4s5kFu3jm3DkriCW5td76a+Vb24jNw3f8aTUwKGiuk1cWqJVLQwYlGO0CikVgWiMxceoMvV9Ze0U5Tmr+wrWo8ELEKIFlMsFhL/9SL7b7mVytWrWdm5B07dQ2xBHqUP/x/pZs3Aypqfsr6ZLiHp+7DqbtKfHU7NYEwTxT8NpnoGTNW01jrHzZoFzvrrpBeupXLbG8DtzHm7hM1vf3SUitd9WaQ5gXCe3pFOcUkuqgnu4iKSTQ92VUVRFCpQKDVMKg0TzTSxYGJRwAbYfHs5YlcARcFUNbAEkp7+A3O2f0Cfc54gMr7xMRy1aYqCrirYNIWFi/bhahNAWXExkZUmmTuLYNzRclCOuB+Q4TEpdFqZNeVvOCxw0WWjiezcl7L8bBZ8thCPpfE1tppQ8lFlvzwTvSwG06MBOmgmRWUFpOs6zVsTuLpQhcaWjhmYGsV2bTvKgmyMK40Gp7gfPpv6tXm7WHugEFWBtQcKyS93Ma57PDcPaceAdhEtqaE4TiRgEUIcE9VuJ/mNN5gx5hIyImLJDQ1n9MrFBO7cXesOptT645te6kbFmajiqMjA9F+oYCpKrTSK75xy2Guo+mmt4NyrUGS3omJgsZQR7i2us5hbNbPRF6DgZksbK5kB4PHo6KZJmc1JicskxPD9BrcbOoEKRKgKhqLhNk3cQDkKbhRcioJbUVFME0U3iKwsIijbit5mFWs2Xohl1UAGDHuO4NCjL3Jp0aH3liISdh3ErYDNBK8CceObMLhZUY7Y2hH++z/x5b9ewa1buOml/xAY6xtnEwnYPlqF193C9V+OQi+rJOufX6OXxYG+j6R/3eA/t/bejynzHP8+ochgOwyOxrIoh9mbsxnTs+5+dQ016nz8635sFpWUqEBySn3Lcczbnk1cqEMCllYmAYsQ4phpQYEEP3wfC37eiRYUReSt5/DXWyccPeFxMP2KCbRPasfYl15jdAvz2LhlO5OzKvgi0OTcgb65v3Hz1lHqCOTKNXOJqywjNiaGa267o0n5mabJU089Rc+OfRk6+GFWzn8Ul2UBvy4fSXL0U3Tpex0ARXn7yDywlKj43kTEdvN3JQUYCmgKgQ/2Jz7MQXp2KYbHpHfS0Re1O9IibACOoRdgmfoqSREx/mDl+KhZlKVk4XqKZ23FKC7HRENRLKAEgyUWLbiIyJuO45IVRxh0CxASYKUCOJhZCj3rnssucZGRU8J7b/3qP5Zb5uaWISk8PD6VES/MJ7OokuSIAGZuymRXdilVy7mgKgo3D0lhaKfmj1MSLSMBixDiuGjfsR3nf/wGNz70KtHJ7U5aub771TGOQ6hOX+sXt7OijApnILphUuDRKTyQ3qSssgqz2LjPt8Cmx/AQEBzHeRe9TUHWbpYvv4T0gsfInbUAd0UZRtAyANILwLvKQVTwtXQbcDsmFaihOuERAQC0jQtp+ntRNUy98R2mv3vsQco1FcVb/xo12IpmHEtLh0LOf3/GtS8AwxWIarOjKAagg1pOyMhYQsbUX738WEa+Hm3sdsbuIiKAIT3qr7SbV+omt9JFZFDN5zu2exxjuvuutWkqhmky6Zy2LNmZ66tqVZfm0t15JEUESMByEknAIoQ4LmJTOgCQvXf3SQ1YAEzj2Gb3+OOVWn0EkV4XHfIKeP6Bv/D6358iy1D419+eREVh+Pmj6XPOkFrpTYpcRazZtYY5X8/BavgWjsvzZPuvCY/tQL9+77Nq8WTMyNkQAN6SEBJj/oiul5BV+A2F+rssXf4uWCFrbwun3KoaptF4wLJzxxYAht51bwOfQ/UMpeYzSnxdSa6yAGAvbZ67DtXW1FuMWbMNdnMdZbCurkBxooNO8fVnjplAQqiTR67t22BawzTRDZNJA5O44Zy2dc6NfWlhy+orWkwCFiHEcVGQ6dvIMCA07KSWe5QegSbJrgp40mrFPW5VQ6u68fcacBaLFy3CNO0UenXWr1pFQJtoPvrhIyrKK7CUWbBXbTNg2Aw6Du7Iobe+wtGl7k7NMW36c8E1v5CTvgmrI5CwqNpjUu4jffdStm9+kZx9+4ksa9og3cMpmgZHaGHpGp3I1pwMPpjyOHHOIMZNfoLwrlUrvR5l/EtTWCJziPnzJNQGtmpplGEeNfBoTHUXTWNMs3ogd4Nnj1jseZ2j2ZldygfLDnDTkHaHpTxyWnH8ScAihDguVkz/nJDoWJJ7NG29kOPFBLZmp9N32RLiBw056vUNKa8KVN48lM+1wKqMTPIdgZRkZ/DsE4/5ClE1vLoXUKn0uHn3g3cxDZOAiADswXZiomJIiEtgeL/h2DQrL78+jdxvFvPxD5dXBQI1WzqbUHOXrX0vrTqW44kjwNxA2v3T6la0sTukP9AwMSo8eDNXs39s1Wq2pomOhUqcBJoldPKYRJQr5NodbE9QeOfJBylxRqJoFuzlhVgdCSz456/+mTdGVYWrq6nUqnrt5zGqQYEri9jv/8b+75+o201X+z1W1dOLwtLoONwWO5VqIF7Nwcs3/tJAghptnO3pFjIQzVKzb9VFXhNdhaXPLKn9Efq7CmMyfBtQ/u+eebXHfKMAQV6DkiMEHZf1S+TtxXvJLa2/F55h+saxiJNHAhYhxDFbPO1Ddixfwoib7kCrt3rqidXvnGEsWrmI3C2bWhywnJ/aHpZtw1lWRlZhETdt2E2QbnBubhqBAU7/daZp4jQMMoqLUVSFa393Lb2S62/QU91FZfPoWGyaL1hR1VqznWrf/mt1w1Td5GOKSokuLkZpV6vlwTQb39HYNKt6VBTU4DYYpZlYQiygQJrahdVhvlVnrelfY+MgrhAbHjSSMrNYH9eWA9YYOkU52ZMXSXFwB7qF26qCKgUVUBVQUFCr4iKjqjpG9ftQYE2gQo5pck9+9aa1tRaDq35SawZYUWUxeR4HyYGBKLZIyh3RaEfZQDO2LAKbolIZHeA/5jYMihwqZqTdt9lurfqZmIQ6K4hTNOyq6j9fPct+RnoBniMU+e+5uwBwWhve2FfClZNLAhYhxDHZsmgey6d/RlhcPL3PH3/Sy+961TUsWrnomLoynA4HF2bsJU2zctvClRQGhPN17zYMvLD+Xj5Tpk1B3aZz/sUjGwxWABRVpSsloHi54MMZza7P7gsm4Kk4SJt/XtvstHvOfY6glGASv/BtuvhNrf1zPG0uY0vbNNqEu2kTHkBgoJOAtALu6dmWc4aOpu8r89EUhfG/b3ivoSP5csZnlGMl/o+/HP1iwLp+PvzjBQbffBWJ517epDQb/zadyrJyuv95TLPr15B/PzGLOEfjY2dmbMoEoFtC/UHPJi3uxRItJAGLEOKYdDprEDMAq8PZvHELx0vVYmAtHXibfWg36159Bm9Ab9YPHg7AkMJDDIhreCBm+zbt2bptK4GOI7cGmAqoLQ2ijuVOqJhoIb7F3w7ll/LPsAoAJpba6OjVaOPsyq039SXcYWVL1iEK4g+woKiQn2b+iKsCApqxaWRtFlPHrTZ90TlT9+0dpKrNuA21fExwg1ze/TjKcnjwqaX41/mptebPxTYdDxqHcjsAMXXSmmbdQdrixJOARQhxTKwOB1c+9g+++Ntf+fLvj5HQuStJ3XqQ1L3XSflCV6qCpJYELKZpkjfiQpKADiPC/Mej9u7k8aoxEaqh4rF4CG0Xyr1X3MsF/S9gy+wtrNq5ioFdBh6hYgqK0cKI5Vj2WTJ9M26efPJJPKYK9AdgepCbvxTaefNQDq8++QtR0V7y8l2Yet3AS7HsBpq/a7LVNHArTQ9YTdM3MFhpYPXZxiiGgtnYsrYt0MVShkVRCYlrW9VVZGBWLRSIaWL3uLAUprF21tckBF7O8L5datVfBt2ebBKwCCGOWXKPXoz+/d1sW7qQDbNn8OtXnxIen0iv0ePoPnw0zmZuRtgcquabQnykqbyNmXvlpSQAmzsncO+Tf2FyVBy5hbksssazZUcBilXBVeLCkmOhclclq3atYliPYXjsHg5lHzpy5sd8M2thBobhb6GxKgbjbVuZ6U3FG+Hg7XPDsC/Mwg3k5liIjSrkqoHBXNi1D1EBQZz/5WQcAS2c1qwoWM2m/xsYVS0szQlYMDmuAUuqVSUkOJZr7rim0Wu+mrucjQtnsG7T1roBC75xPeLkkYBFCHFc9D7/AnqffwGmaZKxdTPrZ89g0Sfvs2Tah3QcOIiOZw2ifd8BWB0t36umIWrVxoVGE1tY9s6YQcX9f6YiOJiEkhIAtvYaxK/vTCUyJZLJ10zmyqFXwtCaNG//8Dbpq9KJCInAMAwM3SDUdvRVZ1vsWO7JXhdK7haefOdnbnjxBtZFrSMIyEn+kCTzV+4f+08eX/owb/z+AnrEJdZJagsuxGppWZeQCw07zQgaq/+9tKbfhhQTjOMYsHhMHctRuqQuH3k2KxbMJuSw1jKjVguLx/Bw2y+3sSN/h29huap/QNM0URWVJwY9wbiUo24CJY5CAhYhxHGlKAptuvWgTbcejPjdbWycN4vtSxeybckCrHYHPUacz+CrJuFo4ViJw5lVAUtTf+sWb9iADTBioil3Oijv0omA7uGU7c+hMK2wwTSDeg3ii1Vf8OU7X1ISWEKwN5hOKZ2OUrEmv4WGHUN/gxLs2zNnXdQ6VEMlwRXNVLNmYOvFXd+lR9xt9dKZpoHSjG6d2jyKiuUIWwLUK6sqYGleC4tCozsdtkCOXkhOXiFXHOU6RanegrNGuUtnZdYy3li/gBWZK1idtZqJHSfSPrS9vytUQeHF1S9yoOTAcavzmUwCFiHECRMQGsbZl17J2ZdeSWFWJlsWzmX591+wYta3uK0GqqJSd2PEGtXjK83D79uHvVZMcKJQVFnUpDqVL1iIDYh74AGShg8HICU/nbdfeZsKe0WDabond2fX2F3sTd+LN8eLGqwyuu+Rdy7yWlQsx7KiXUvTWuyYgb4BouuvX8tl7/djtzOL/9s6gIuCrAxJ/JUB4Vl8tOhyxvT7NzGBCbWKNFBb2M1hMQ0qmzGA1h+wNGOF21DPidl88Mknn6x74LDPfmCfXwgNfYdZcx4AQFVMnh8C2ypVXl1X02L4yDmPYNfs/tdLMpZgmAaJQXVbskTLSMAihDgpwmLjGHzldUQO7MFTb9/l37OmT0wfNEWr1SJR3Zxe67V/zbWq56a/0R3T66XDjM2YgU37da/k5uKxWIg/5xz/sVfffxUHDhK7NH5juWTQJU18pz4Wt7fFjQGm243p9bYsse7BzNhIafYBAiITebnN3WRWTqE0aVWdy+I969i4/FzygsZx1cDXfEnN6iCy+aymTjHNGHTrb2FpXouOR3E36/ojGVPZlf3GAZw9ozENE8PQMQ3Dt16LYWCaBoZhEBrq22KhxP4n38Bc93eEK3uJibyIRSMfJ6s8C93U6wQrAOtz1uO0OLkg5YLjVuczmQQsQoiTqkvbXnzytyUsyVjCffPuIyxe4V8jXsCqWluUX0VFCfveHUi21rSWAVNRKAwLY869fybDU8GB5HY4FAeKbkOf3YGXZ8/Ebavg8gcG0D4xqUV18hUEuq2F3StpaS0uVjcVFM3E9p9+eFFpi4sYu0pmdCjBgx8gILwXOcW72ZXxNwBUo6ZVqUzXKa70tKhcDRNvM4KdmllCTf+MCtVcTFuzq9aoKCOY4Ngu9Lzh4iNeN2fuVABKbGm0Kf0SFMjwOrjx7H8BEOYIazCdqqhUeCv4audXXNH5aB1P4mgkYBFCtIohiUOYOmIqf5z7RyYvmsxz5z6H1sxf2wBaVTdEU2cJmSntCNmyleiF80gGQoddTrFehscGSpdKyrMNAnZEMvPH5dx9e8sDFtXwdWqZHk/dKdeK4hu3oaqNjt/QIiPR8/KaVI5hGL5WFV3HxKBID8aFg1AyUYAD/R6DTZ8RmpFDUVY4oXY7bZz9eXRfMKHWIP4w7B52pa3HqlhQvS48lgA2px/E3kjs4du7R/UPLK2WVWnBHtD0YMc0mz+GxTRNLIadyl0FNZsIqUqd8T61l9+vs3cAta6r+qOiAY3XucDtQfV6/N2TxauyWJR9AwBh0ds52H4DqrXmNnr4ruEjnX34pMSkJGM/ntCajTBLK3dijYzGYgmq+hyMqr+mrwUHA0yjwXNgEhSUiqY5OdMo5jHvy976iouLCQ0NpaioiJCQZmzDLoRodXP2z+EvC/7C77r/jvv739/s9LruZVuPnr4l2Ru499nbDCKg940NpjXLc0l4aSKWWkuv5xUWMO3htZwdqBFrBae6gDDbiw2nb+B19ZgbuwnF3isp9v7uiPX3BVpVa8VTtfy+aeJJ+5WKHZ9WZVo11tS/rnxNgUq9QT6wpWtXNvauWYW3LelczfcEUOk/dmdsNEsC6t70CmKfwmtvD8D1X71OfE7GEet+uIIO7XnmH6806doDcz7mizc/5eYnHiGi2yD/ca/XTfae3ZimSWxKRyy2miaV3Q//gp3je6MuCymly1/rr9D8zvLV/LW85n8XHcwdnL9wi/91RG4e58+e3aIyD/7n2Lq1kpJuoXOnR44pj1NFc+7f0sIihGhVo9qO4p4+9/DautcY024M3SO7Nyu9plkoevpuytL21jlevUaGmhNLslFJcJu6G9iVZ6lY1VgMt4G3VuNMqCOEix/rStnUnSgoeJU2bDjrhpoWhXq/8cyq8v6/vbMOr6vI+/hnzrl+4540aZN6UxeoQEuhirst7iwsvtiyuC4Oy74sy+Lu0EUKhRoV6u7ext1ucvXM+8dNbprGU0thPs+T5uacmTkzJ7053/ubnwRf1smHocs+xCyysKZX7lVHqLa5ERQlMvRdBqvpSQlS4M73Qtc0bKPGB60Cmhb8rmsIgq+FCFoMhK6DpiP0oANz4cvfE+6v5qSMjOBdEAIherDBGIm7Kpt+sZFYhcEjRhW77dF4TXb8BPDLAH+qFSsAH59+Nbf8/A22ihL8rlJsSRlY4uKJGj4EUWtV2Fsq5X30MimunDb/3nZv2QlARWkpMYCnpoasXTv48smHEO5qoi3xrI6PRB81jtjoaCw+L6NlNSm6ibipvQn5Nu0l3uqONfgN1Ym8BseCP5f+vB2vrbGFpbzGzfLCEnDGc5/u4vGAk2dW/YvsAQbr1k4AoEtecP6FV56FpUfKXr33teJo9IjuiVWvF145/iuwVyfQZ/TTQadjUfd71RCIWkdkrfZ7w5/XrruVgL+qzff594QSLAqF4rBz+YDL+WnXTzww/wE+PvljzHr7/FnGnHtTs+d+euMTyvd46HlTQ6fZrZ9swryigIJHf2vURwBhtT4xmm5i2MmvtGs+AN7129GElfjr2+9wueO1j5BVNnrc/mq7+1a++w1d+9npe1nLlh0nDZPNSylxfv03XFHnB89XVxLIWoc3oGEyh1G9azXVu8C9eTuTr72e8LgokrrXOyl//fnTyHY8UmITghE/hhS89fIL7C4sRuomyMjEVl7GnF6D+anfXuURTPCv2GrKcXPyuNQ2X6clCmdsgiascsNmLsXljMfk93HT8cfQraCUMXNW8o8eiaE2peHxwFYShx1Pn4ktR4zti/6liTB3GrGxjWtVtdpXdzbajvujoASLQqE47Jg1Mw+NeYgLvr2A2VmzmdRt0gEbWxiyyWRjqVPTydJF0LJBQwNI3c/h21az1y5K+5BG0L+ig107XIhIq/cPaQ9CCC5f4MQXNpejzj+fE8b0x3n6CaHzbpeHpd/OZNFX/2Hac3cDcMY9z9Fjr+yv7SEsIgxDN/Hh/37Bb7WTGhPNwIEDmT5zJu7IKCJdpaG2N1p83DFqOPOWLcJwHtxt/yu/+QFXRDJ2dzXv9QoKlNMSotl5/VpefXE1l9uWUGA4eTvxbK4f5ODuCRNCffPz8inMykbXdDRN4K2qYtsbb0GPHoy7/hp2rFlH8Z4sLHZ/h8PWhRDNVu3+vaMEi0Kh6BTE2mIBeHbJs1T7qjm9Z/vCiJtDStlkOndbpJWe5/RusW/xs0sxPPtR06cDTsShvh3NGydEfRbZdtKjtAfhbj+n9k1sdM7mtHLs+ScycMJoFn/9E6tnvEtFUVn9lBGIdnzyN4Dq7v2RCM494wz6DwvWPMrol8nH77yFs7qczUO6Mem3dfzPI/i7JjBrGp4DXMCnbrQ9lVU8t3Ap30ckc2ZlHvcdcxSpsbGhdmERQXvU2+4RaLXrLBs4ukG9rHUXXERyXnZofSagD8DCeeR+8C4OKXEA+Y9AnmHQdK3vhniXv05p9rfIiBQ0KTEcnqBT7h8QJVgUCkWnINGRyF+G/IXpO6fz4IIHmdB1AmGW/c+GK4z9SOe+H8LBqPaCNHCVVrJr9gbwGogyPxnnDcUWHSw46CqtZPPnS4nslUBEQhTWOCfhCVEYHn/HM7oKOl43EVrNsBsZF0XvkcNYPePdBteRfi9aO+YcFhuDNJk5Z9KxIbECkNAllZv/dn/o58viI3ik0uDD9VsYUeajPHBgt0MMIfhy0zb+uqMAj+5kQlkOL582GfM+JQNi7JZQ/SADsMT/iLsojOWffgFmM9JqDYkV91vvEDAkfmnQZ/BA3KVlLP38KxKOPpoBgzLZsGgCVZH92jS/PasfYGdXBwTWBg9UgdPZ8wDegSMHJVgUCkWnQAjBdYOvo9RTSkF1AXbTAYoGMUB2dHvFYD+KGEqMmgC5Ty8mYq/kIdu+XkH/K4KFilz5FcRvM8G2EtyUUI3B5u5+EvMz2B61lA49lg7BlkGDpH51B9wVCK3t1y0srwYgKiaqxXZXDe7Hv39ayEu7q/jSK3EWdyxPTNNIvjVH8XJOJVjt3CequOnMep8jwzDYXFpNtsvD9R+tCP1X0MM2YI2bRX5JGPYHvmo0ao/MvkRE7rV1FR7GqbfX+1kFTGZkG8O5ZZfhmL3r6BF2Ihu9PwLgrtrRSq/fJ0qwKBSKTsPXW7/mww0fcvOwmzuUk6VJ9qNgnpQgOtjXJWowy2hqUnSip/QkqnsC2X+fT+QmWPnMjOD6BERjxkcA7+RoAjMLSNxuI0crYVPkLsZ15MIajQvftJm2bevotVFCNRW10SpCYPKbcbrcVLzxaMPG+4Rd+0srEFYLubvySC2TZH/7E5UL19QLw5CFR4Am2FVVTXd/UPAVWXtREWXlwLjcBjnWU8aXbkGRD57e4eWZudOx6RpoAl+1H+kL3kxp0ThqRCIZ4VlMz/om2HnCOei3XgFeL/i84PUR4XQ0FCtNIGm7qLSH9cBXsyEkVgDKXKs7ttgjHCVYFArFYceQBi8tf4k3177J2b3O5soBVx6wsYVBkz4sbZxYk1EkbcFr81MdFmDgTeNDxyotHiK9NvRqiTS8mPw6YMaMTrdxA5DHSgo3ZrNk7vdYTPuR0rWDPixB60zr96pLrzR0SzRLpr3PoAkjCYsOJ2mbi/BiF9nrPmzTpZJqv5i/oMV23YAna197pz5MRXjXNo3fVmI0WHrisZx439tsIIHkbk7CbDakIQl3mhmYGEGszcT5mclcPe1epuf9jBARSMBpNtE7/uDUN6qjy+iXSPY/jSG9VO7+juW77iMxseXMvL9XlGBRKBSHlWpfNff+ei+z9sziryP+yqWZlzZwZNxf9kuwSNHhLSGBbOQPkn77KMxWC6n2YM0ZI2CQu2YXmhBopqBFKWlQN0wLBYHAfoiODiKBHVWlvH7TXehmO5c8+TfM1vr6OIZhoGkamknnhCv+wozXHmXtnFWMOuNYNN1OVUYsQ9/6b+00ms5Xs2XqmZhio8n44E3cfomhWeszxIa+1/4jg1/b738a66JfQIsi3XNgnW5B8MB/vmNDIJ67htu44dzjmmz17cYl7PL9zLExV/LslBsY+cn4Dl9RttPRSDNZ0bAS3eMCosq/CeZs+QOiBItCoThs5Lny+Msvf2FP5R7+ecI/OS6t6YfFfrGfW0LtyBzfqLPcR+04o8Ib/KzpGl2GZDTqqmngqfZiGAG09m6NCUKh2u0lv+I9ALzVwX2l/9x4O4MmnsLIMyewe802vnnmToTmwOpMRNSGbPs9tbWIpESazZiSWi5nECxLYEJP7IYTkIZk6e3PY531KeZLb8CXX4h3zUq08iI0bw2G2Ya9dDeVCX0JczoPeAaSf+0s5gdrHKfEVnD92Y0z3tbxzpovIBDGC1NvxGYOWr86nihedDiXipTGfonSIxklWBQKxWHh690ruOu3V4BwTux9G4urBEs3/BosDYNEo7ZMDMFdGX2v0jHB/J+gCYmnpJAwVymattdDIPSBXTI2LxiNseN/CwHIlhrEJaHpWl0jIsrX0J1S9H0eBOaa5egUw4zmnBz3DpNp+AAKD5RSYqTQFnw1NexesIC8rdvIyc+j0AMxRR7WnzAEfWAqWC0YecVIDEy90rD37Ef4wNFEZB6HyWRrOFgzz7K8rHxWLV7Pum35bC6pYavXTLUhGFW6kAxfPvHOMHbZ09hp74otKo54w0Xvwo0s/upfLPnmbSyOoF9GdEo/An4vnqoyhO4kLm2vEOg2P0jr71XupiKc098IWqRefwpNs0Byb2RGXwI2B7K6Cm9aOsl/Op/KZc2vryPMRmOBNZ6LUqt57MYLWrTsba5cSDfr6JBYwahhXvYc7l4ajy50NKEjhI4uNERAYt1dSBxxoYzLdcWNBAK700d85f9YvdaNJoKFIKUMgAzWgwq+NkIVyamrJYRBRflmqorCWLhjO7OLK3A7PyAjroxztGTCRAwNyzzs8xoJGcdBt9H7Lu+IQAkWhUJxSPEZkvu2ZPFuDhAfjJz4pArocLbxSJBeTO5sdF8O4cX/ReAPnX3f9ASx/ijM84PH0gHYHTofrn9KpPndJke21iXcnd/+WTkBryevxTZel4vpL7/MKpeLgCn45zjM7aaXkPQemoBGIoHNueA3EHEOhNAITFtDtWs11XxCnkkiw3QMp0BE2NHTE/hBH8pv1f0Rt7yO0+8hX9jIskZSZXYAYPdbyPDX0NdcTZTTgrmgCK+/huzyGroBi2JGoUkri0nG3y+FW8ems+T7/1BZuAOwcuZdNxOVGNvEaupKBLaF+nZJvWMo0Uz4T7mMPnddjTUqLLQ9ti/rls7vcLR3oNqH9AbQwi1UL8+nYsZupmp2cvFw/19azkZcUFVGQFTQJ67eGiYIYPFu5ft1TzXZRw8ILvmxaX8bcZ2NBAooLPimlVk3vp/+mgiKNqTw7Z4t/Gb38t/JX0IAduV66b+zttqjqC3lsO9rdxnsXgiXtnbdzokSLAqF4pDydnYR7+cU82jPFE6KtWFg4DckfsPAQGJICACGrHstCcjg58tAbcmdgJQYUvLCys0sNkeBsOC3ZOC3ZPBsbCYj02u3JYSASRKn34lJNzFj0xb+7rVxhajmkhHDKKooIPWdoFjZc94PpMT3aDhZvxtNVCL2DrFubY+o9lN60f+diMvelehmmuVv2sTHb75FhcXMILudgWPH0mX4cKxOZ4vDSynxluZRtng61VtX4ynOweTy48/NJ7Aui3OH3s1UIXmeLMpEGN2tkgnhkox4wZAhPcno3xO91rq09OcZzNlUha/fWJK796Dou7f5+eFzCA93cscLn/JFvpMfvy7k1O42zhi/A3dxGMVFs4hMOBshBNM++5RVa9YQ0HSYMIneuTkc3fLdCWEYBtlzZ2Mu2RUsqlyYgz0ussm25dmV7Px8K1G+ALrfIOveXxE2E3q4GYTAcPvRwy2Yom2YEh1Y0iMxx1gxagJUry2iemk+RuU+BQdrf409k1rP9XPbj88AgnP61m8ZCQSjU0bzyoRXCBgBAjKAz+/jm98+4If101gXlsN1b36IzRb8fUpkyMgxfPocBph3c4b1bSJkAVm2E0iOGcHQlEl0iWg5Bupf188E4FgAUS/MN5t1FvYbx1G9TmFw5nlN9vU+P4nAqlXknX0O7nXrsPbqhXDYibn4EopefRVhMqGFhZH09/uwZWa2el8ONUqwKBSKQ0ZASj7ILeaE2AiuSWucTbW9/LNyBcREMao4i99iUxlamstZp09G1xt/Qq9we7hBOMAKPaMjSIp1kLe1vo5QTtEG0jLH7Pec6gg08ee1srCQbT/9RM6ePayoqsImDS6beiJdj2n7dYUQWGOSSZx6RZPns+75lWgEj9KVPb0iGH3l4GbH+vXDtwDw7tpASa3pYvW6LRwzaggPXX0S+ts/8Wm2laKaVOKst5MlXmdn/t3s3PEmx5zwHsvXrW+QzdcrdHyFhWg2G8JiCX41s82y+6fpfPHW/wEwiQBlW7L51/UzufzuLjgzgun+PSU17HhvA7acKqIR1ERaiUh0oPsM/MU1+Es8gESYNHyVVfiyqmBNExczCWz9YtAjLASqfFi6RhA2Jpm1D8wn1mFt0PT7BY9idb+NFvcixw86NXhPyn6lh2MCo7s1zoxj1syYtaApbv6GGTy7+98QBmEeM1aLDVMT/xeF1LB7kjhz4nR+WPcizpIZWHN+YmnOi6zv/gKT0k9o1KcOXXcxaOl/CJhsTIrazJ7a4z9iY37ZCliygrmJw4iObTxXX14eVLtwr1sHgH3EcMo++picVXcC4BwzGteChbg3bFCCRaFQ/LF5N6eYjS43z/dp2TETYMaaHKq8AcZ2j+On9bn4gaRwGxP7J1LjqmJVdi5rrcFPx3/qmsTXRw8BhjQ7Xu+FG5hYvJAR1dsZN/weAIaMvAD/sLMwPR6P4fc227fd7OXPUrZjB79+8AE5ZWXkORxITcPk95Pu83PGzTcTlnogs4rAuoCL/nqtlWZXZYttz3rkOT6/4xrMyenE9ehDwfp5ZGYGH3Th4WE8fdNZrHvuTSzWOAYfczUDAtex6MdHqDJ/xKyfTqBXlwvZkl1fbMnv87J1bDPZY3QdYTIhPR70uDh8/voEcAt6d0Wz9cBfs4g3HovnimcSsVoc7Hh2GdaAQXWXcDIu7IM93tHiegy/gS+rEs/OCowqL8KkYekRha1nVJPCyWRA0dYy/vPflbjcxUwvzuOusW8TX+Bh06+vctHMrcSkrQFTKanhSY0vuM/2VHJM8Hd5vDGEl655t0WfGCnBYrJz+uB7gXvJdRXwy/IbsG3/M7Pl84zPOLnJfjZzKdHlWwEIFMMjm+IpcbgQUjAmfzQVlgpufvthLu46iOqcInKrNc46ZSpJA48L3n/ANnAgaf95DVN0NJa0rhT961/EXnMN5dOmYenZg4ipU1u8z4cLJVgUCsUhYU1lNQ9tzeZPyTEMi2x52wPgkqKC4IuVxfUHiytgbkHox2hgeGUhmT1bT3N+sdnHs2uDQmXRyn7EjgvmejGZ2lcZujm8K2cT+Og6zFoBmkmSqEuWF4fz7htvoElJit3OsdHRDJw6lfi+fQ9o6PbevOLN5Vp7OkMxUeVoOcKoW2oylWFJhG9bSsG2pQDo+/hNaEKGgo503cSYkx4ha/tE1q65mcTur+OqGUxOSbAqTqTLRfTFFyO9XryeGkq8pVj84KiRiOoajKoqjOpqos89B29KvVBzWXWQq8Ad3Gr56c4tDI87CQcC63l9yBje0BrnzS6k8LVfELpAc5jRw63oEXa2+nPY6S3DoUcxZFM3dkTkkpieSW/ReGPOV1SBzQiQ5AmwZmkxFgQ3ZG0g5SMLKweYeOLUPeiB9wlUeeliGshdx1zaaIx9I326Jfci1uNknbG1xd+vqO29N8nOBM4Z/QEfLbyCqB1/Z0fccDKaEEnV/ljclihs3jJKo6IYVjSCn7vOpk9ZH5JrkkmuSQZg4ToXENzK/PcXs7j153sI0/PxR0WR8eqn9eNtjMcx/gkKX7wFgF+mPsoVfhOtv0MPPUqwKBSKQ8I/dxeQZrPwWK/WLQrGXjlIbjPs9I11ckyPOJ79dBVRXok/uoSk3qlcMHokYTZbCyMFkX4f9/94JtQ+vz1rv2RB4SbqoicOxEZQ4KOrsdsLqY48CSkFlRVZFGmZjIiLY+yf/kRYQsIBuEob5gFM13Yx5cGLSTG3HpM9/vLr2LxuPRaTTmJyMhERDR9VmmgcJZ3afRyJaQtZNf9ZuqZ9S48BqxBucPg1PFfexZMzb2VFdSnVe+22RNdoDPenMjLxGMIdLvZ8/y82p1biNRtk5DpxuoOPo96RRzEk5vhQPzlrEflzakPEaretvDuLELZeGP4aAhUSX5ENITRS6EYK3UJ9MyqS4e1Sdru+Ai0Awo/QJEgnwhqNVrSJ6N2LOW5AOtmbKgCJX7ciqjycNzeAkMGQ7QExPlauvJFVsn4aF5T4KZ1Y0+C+PPd/t1Ac4eLmLq0nPmwqItpmsnLa8OeZ/9tUfll1N1eOeQttH58pe2QFC8Y8TkXkBjz2QiIDcPaOs/Hhw5CiyXpOyeQTVr4Jkx5gS1gSe8t7oUWCBsIazj9PPYMvJvSk37xLsUTupkuXC+mecXOrazlUKMGiUCgOOuU+Pz8XV3Bz1wQceusP0b0/nd42ricWs05+aTXVuqC71+D8UUOJTE9u07WNgI/dT44nXQ9uj1TrdnpVbIaKzUgEUgh2OboSlTKgQ2szyvKp+fc1OO2FVJtG4LjtIyAYJdTEJsJBRxL0J7VY2/bnffzYoxg/9qhmz2uaJCAbWwvMZjsjxt8P3E/ursXs+u/VuMa62LrxXM5NAfOWDE6OOgWv30O5u5Rdvu0sDGzm5+rdUA2kgegSfPivy6jkgbS/MKzXsRT+ZzWVWin27F2Ykofg3VObgE9oCKEHo15MXTE8ZXR5ZAJ6uAPD48VfUMqORb/iffqfmKpKqLT6iZCRmFJHIswObP2HIH0CGQDNXoUlzUTlN69gkwG8RevoUrvGCruXLsXQpSRoPzFpJhCbagtDBu+vBE4vlaxJqIaL6u9JfEIquKG4NA8pZQtWlsZJBesoD5j4Qr+cS73/5M2Vz3Naz1PQhI4udGym4BZol0HZ/Pn6P7Nl7S6+/PJLDGlg8mlQnUJhdA7Rsn4r8Bo+pAv5nOp5jDRRwEZHd342DKp++QXbgAHUrPqI3KT+vHfmefzvuImYpYeuvYeTO38Z2dkf8qFxDkvLXfxW7uLfmd04I7E5N/KDjxIsCoXioOIOGFy9bicacH5y29KYC00wqUZjht1g4k+r2W4Dvyagm4VPgTXr1/HPNggWWbYb7cWBpAOFRgJxD23Eoem07AnRNqQRoObtv2Ld9g4OPYDLcTyO29qWlv5gIkXTn7I7it6EhWVfkrsdTfKjq8n59b+sK/8PmqOYO899lq4xQxq1dVWU4KooosZTRVyXXpTk7eGK767gbwUvcV1WFqfrEyjrWoF39jSEOYtu//1Hq3PUrBYsaYn0STuHrMxubPriLQJCkrVhHdaUAgZceRtd+jWOXyp66S7sg4fR78MPWr8R7nK8AYnZEYkQgt9GZBJli2rQ5LJz72bRu6v5oPp7Bi4cxsljzm9yKJfuZr7Fz89525iY1DAy7Y0dq/jRGE8/FnFU2ausWfpqg/PRlTfhXe/EX1VBn0EZ3DvoDopz8njzmVm4vfHMMXTKPA7+ZX6FIdo2uogCVtt6scbdnTWyO0NKtrIps3+DMd8e05Nfh46n165iHpkUi3lmFfFPmYFyEgffzW/X3wFAjudAFp5sP0qwKBSKg4LfkPxSUsH/7S5gVWU1Hw3uQbK17fVxXhnXh3PnrGe7BcwG+PcyzHxmj+OOwiLS4+NankNFAXUeKjH3rUIcqIKKQPUzZ+OsmYXL6IH54tdw9mveSnEoMdpYwLCtaEJiGG3zt0kZezXbtwg8e54gYDT9cHNGxOCMqBeuzvRMvr16Fve/eSun75oAQPyo3pQ3nRqnVVIzjyI1s42/i0CAQElJ6+12/wZvTsEC/Dvhca6/4S9NZtbXNI0nznqZ4746gc9WfsDxQ0/GYW8cNm2q/JDyuKu5eEMlaRu+IcZsqk2WKFnjDgcdzh32JFtzvkYXAkMaBAwvxbkfcHHMgwB4nr2fpeevxmbRmffPX3B4kzF5VzPFtIGkzFxifdu4x3YbM2LHMLVgNoO37GRgzRYu1X/CHO3FXVr/Xhy0eR2Za2cjMFj1q42k+etC5+JlgD3HDSZj7irsbbCOHkyUYFEoFAecCn+AM1dsYV2Vm/5hNj4a3IPRUa3nu9ibyDArP508tMGxcf99n809BvBatN6iWJFGgLw3r0FWFRBvaJg1A/3JZHyGhikqBSG0UObRBtWBh10KY29vdW7eNXNxVM/CZRuP86HOlYQrzxxGiqw+YONpAvxtFCwAWm2Ir9GMYKmjvLyU7N07yd+5B4p8XJZ9Bj7hJ+me4dgjIyiH9pTb6TDenTtbb7S+/necV1BUf7yJbZ2YiHjOiZjM5/zEqzOf5Y6TH2rUJrF8M8d53kIMuJAZJRrFfhnM7Sw0NHzEGnvoEt6fHpm3Nuw44G6YH8xVYxZuznlvCQBnGgl09a+k2rmZ8EAk5Ajye+RQFSaw+nxEu0ZxdIRkqFFGdI2XolILpsxB9PriY9aPPpqANz/kau11eciKSyC1qACP2cxPd9zLEI8XvwS7dnhLAijBolAoDjj3bs5iXZWb74b1YnikE1/A4NfNhRyVHoPN0nErR5UzgsydGzj9+AtbbOfK2kBy1hdU+B2UB+xEmGtACgwEJk/FXi1l/UPRWwlLXm9RsMiactw/vY9Y+AyGpmO/7Y0Or+VgUaHbmG207ojcVoJOt+0QLCL4WAkYTYeJb1i7kqovdpBcE0cEEEYkhdYySq2VFPb1khEZcSCm3cbJatiHDWu12SL9aEbyfw2OtXRHzJoFS8DMKOsw3vjyKV6s/ICBnq68fN4bxEUlIZHYheDF4S2HD/sCHh6bdQmrSnbQKyKJp6d8wxOV/+Bjcywu6n/HYdKgKr6KgCWBHt11cnINViw/hcHkM0L+wGWeOifmcbzGSBJT/sNpN91BoCwfUVYF3eqjsGaMO50deUXc/Ok7WH0+5u/JY1R1IHi7DnMNIyVYFArFAWdGYTkAj83ZiiZgmwiQ59Swb9/D0f7gn51GH5730g7FhS5qavzolqAJ2nC56GKvoiY5lsyqnWQ/Oba+k8+PdXsORqwTX2xwq0ELuAkDqsc+QNKUP7dt0k93h8o8eK4vWMLgurlgcSADAfzb1+DfMA/Tb49jt1RjmASeMc9gj2p5S+rwEeCEV95qWPQYwC+Jy6okQg+HWiEia2983b2X1LeXwEJzCgOi9jR9mSbQa7fdDBlodM4f8OP7NBtN09h1fDWxqUl0zehBV0dz1reDa2LZlBiNpyyfZVdeVLvmunshGxQ2rKioYC2j0DDoYVvNJ5eeTyAuAVvxct6fOTbUrq72zzHZkzg99yUiN4PLnEbv9BgGxu/mg59OINPcncnJ5cyrWsLfP7kTfasdYQhIFsFr5kqEoeHQNc5wjeFoxxRKjA+4qHQzD67sz9zu3ajMuhZk8L0xqUbHHr4Zr8VgwlGj2bEhiyjDTQ3BdAA+YbBc386wQHcgGCi3Oq4no2+4jMfPPI9PX/2Ifts2EV7lojwsjE09erMntZybP30HALvHjWYEMDQdWVYCSW3zQzsYKMGiUCgOOM+Yo3hqVz5Fdh00gbP2E3qSF3YTaPbTqSCYej5vZxmG18AZF8wjUV3spSYC0kQOJ2xZjNlZiKW6BinAtzlA4YZgFWRncg5RGdXIKDN5UemE9RvbzJWaoN9psGEauAqgMpeaF87GKMnGKrIw2wKYAY8/jJrjXsI25jTs4YfvD3dLWOJ/wl/Vh6KKoGtx8EOxRAhwFFZhlBmUmV2YHA60OkFQFzVMveVA1BaZHG5fx1H2jcD1bbq+EEHBEpD+Bse9fi/zXviC3t5UtvcuZtyUKa2N1Kbr7Q+7YiPw6xqx1a691i9C94Pan+02KwF/IFQtyef3kR8VRkKED016QuM5vJJbrK/g62elLnb4z4vTOWHJg5jD8oge8wQB8hkdFqDKEKwrWMdgX60zcFbttWuvXB0wqBJuBlf3JjfMTUZsAV8lpwLZDHd+iV56DoNqdiEjK/GaA/SNTcIuw9nuyibdnkw3exJ+GYBqSbFWiV98hcl/JkO0LFwR0/nhpG58OulMADZ07x3a3hq83UNsmYuZw0ezNHMgQ9KSmDrzf/g0naEXNO1EfKhQgkWhUBxwRiZFcvG7Wzn/70cTl9p235XXvtrA20t3YwQMnp3Yl3MmBiMoRt3+EVOqq7nk86dw9u9Gwrsb2TykDwF38FNm5OBoHGOOpeTzH8heEDSVO3s7sJztCo29J3c523IWQ8BLbFgyAzPPbXjxU1+EU1/E8/ZfsO58D3vNAjxaNN7oY/H1OAYtpS+Wo05CHKBEcweLQfpC0qO38uzN3zU6t+b5hzF99zFFf7uMsZfe1KbxFn80Hr+3ovWGtei1gmXP9m3kLPwSI7caZ7GZCJ+T3v5U8o7zM2biKW0b7CD7sOjAgPReTPjHC+3u++KlJ5HY+xgmT3g6dGz9smkklBeQTX0m503xHuJ2QFJvF6edtRaAOd8dzQWFY4jbfjabtGyW6Zuo1usX+0vKL7hMVVQYK0lfWkmRvZBj0+vzF4XZdDLCV+IPr1uHhstlMH/FIgAu/es1oWrkHm+A795cQbfc+8ny9eVo7WvuGuvjpjVu4mU+hSIRhOCY0vWMz+mOWFuFFDrvnHkeu2OTOH3ZrwCYjQC2NuQ8OpgowaJQKA44dfkn2rPlPXthFk8u2k4fk4Wbx/YOiRUAPxpmXceaFEHZkiwsf7+cyKO7UzJ3JwDlq0qJvLAXGTMfI1BUQPn7T3Jn6Wwqvr4K81eStWkNoxuElCxIO5aw8Iah0d61v5H93xmEd4km6vFpWHsO6tgNOIxoUhDAaPLcgNseYPb/vqZqzmy49J62DSihPSWSLTuDbXvOicBWGc8eZz7+JJ08cxXeHhGMOO74VkY4dEjocMZhadAgqZu/Kov45Xfwjq2GianfAnBGyY/c73oTZ+8izO4oqv7vefwp/Qkz8kAKynu6EAmxUNINbcsG9MIsvhi1gagKwcQdKUT5BDE7JflaIqQHt1l7lfeiq6srFmEiyhJOuNkZtMxIiUW30Cs6IyRWAKwWnbOuH8HsP3djWck0Yuw+sP0J3/D3uJeHWSaPpqYsCssWJ5lH3U9NeCZLtx/FaRHjSOvVhZiaHjht/UlPTyf1AJeRaC9KsCgUigOO3xv0X9DbkGm1jke+XU88Gl8/cDx2S8M/TX6hYdIg6vw/4X/jbYq+/g3D3/BBs/ue59EffJbUx+6i/PTLWLJwLgN2GkRGOOgSqGF8WDoXD7+V2369i43Ch9tdRlh4MoarEs+KX/Eu+Yn8t35As2g4r/oH5iNQrACYaF6wCCFw9U0lfH3bfVJE8Kne5vbx0YnkFUJ5Xz9dTz6K1MP8qbx1OiZYREBiW/M/ir9cgymmL9bF7xHt8WKJS2TbipPwm80Y9nCkw4JBF9xCoHlchK39heF+g2XaT/yybktwME3HYQS3Ss+emYjNV+eY7qMsOo6B4lrOXqmRYK237jmviCC6z2Cyd5dR9PkWwgrcmKXEXaqx7snF9L+3Pu/MzLdnYdWOA7bRd08BvVKjKSw8it6J80l1Z1Gx1knv3tPBsGFPzeaMwY/Sr18/rFYrpJ7Usdt6EFCCRaFQHHC8nqBgMVuDf3i37Czlw1dWIk0a9z82Ft3UUMgYhkGW38e4hEgCfsnns7dRWuMj2mmmR0oEPqFh0gThl95B+KV3IKUkkLOTyveeo+jTn/FXBx86AY9G1fRpnF7yIgCnZ57DBec+HLrGbe8fy0YRDLeNjOhKoCSPXadNxFMUnK+zbyJdXv8YPT7loN+jg4UuBf5mBAsEBYjP1L6HtGzFwrK3g6rJaYVC6DagDyZz2/PuNBrT8GO4Xa033E86XNNJCpzuALGr5wHz8OuCqjOeIGrgDS13C/goeqoHq+yDsJ9/LgMGDCKzW1dGzFyK1esmujzoLDt43WIudfWkW1iwarIhJRsmXE1YaT+S116F6y2oNM1A89uIBX5I1DkxP4BDSij3YPgNdm7fxdKP5nCsZw9xcV9yTHxwa2+8XEeFLYb1vv78w/53RsfOIuoHM9Hn+jA73AwY0BOTydrcEg4bSrAoFIoDjs8ddLi02EwYhsFPT60gGE8TYNvuMnp3b+iw+sOKXLwCoiNtXPHCfJZU7vOgMtmoyKsvgiiEwNQlg+h7XiHymhyqPv8P7g3rMSUmEHX7s0R/dByloppYe/Cq079+nqd2v0lxpGD0Tj93l/Qg5/1jqd7jBk2Ses/l2EZNwtx3+EG8K4cGDQ0pmxYsNVVlJC7aRu7wrm0eT0gdd0oFv8ys36LbvWsgu3YNps7JpM6xN/haAhey0PiJAf5NDPNlsG+5P7nP673P16XAN8pycS/PZdOIsaHU/EGfVA1EsKRCANjlDwCCMJsZQwTz6kgELnsKWalnEi7L0QmEriH2+sevW6n2dcwnSQL0PxPjkjswNA1hshJlar1koNDNmH0B0v2lfJ+TT3buF7zaT8Ntm4Tb5qA8IgaruxrX0HTuX5kZ6qcJwfppf6b7sdNxD3mVXovvxe+1YhISTQiOnf06GzOOZpO7D13MguS7Z1NpK2AXxZxteQ699k5XaFEcf/a1VFgqeHjNbIReycLM47lQe484x3WkDxqGydS+nEmHCiVYFArFAWfGm+sBMFk0XntzVfCgMIjqMZttO6MaCZbRfYLC4rOt+QAMddj5zw2jWL2thOVbitm5YDcDd+9s8lpabAoR1z1EXfaOihkzeHZVJlcNWcrnqz7gw4X/ZmlvjcHFkst+MRi5R2LIrYiUcBIvOhbn5HOwjmwtYuXIQROCQDPeqjk5m3DWSBJPPrPN4/Ua/TgFaz5l7xii7RuKCHO4GXJsRqhdnZFFSgiUBliyvpiVpp2UChPH9B4WPL9XvLQ0al8btSHEDc5LXOknoLsKiRuciTSMYH0Aw8BjGHxk9SGRCCkx76xCIEmNsiGkREgjGMkjIgnodsqwk2rJoy7GO2QMkhJD6NQ4O1aUUkqBpulojjjak/9VSomonXtYUT4iLI9ZomEElsdiwuS0UWwJxg3NTjBhlK8nsONntn03lPKjklngCxDlMtCRDCtfja88m98cNUjnUgpNbjZ6I3CbywD4pPw++kdOI+nUe0gYeiL/+vhm5vvmAGA123E4BxHbp5zUHicQFzeUzooSLAqF4oATk+KkJMfFn2+ZwUBv8M9MTJ8fSRj0JdJbBTRM1hUTZuXOozP4YnkW2/0+0qMdxMc5mBDnYMLIVN6cuYXoga37lOQ++BBln3yCVYfBERoLurtILBXc9K3knHMeJOqeU9Hs9oOx5E6DhobRhIWluqaKL7/4N8c6rDhsba+mFNljFJE9RjU4tmjp3wlU+5g4sflQ5ymGwXOPvEqRpZjel2Q226453t98LomJDob+rd4XwxcwSJu7GoARXsEuYVC5qIC+XSKYfuXoRmM8/vA8TPkeTnvpwia3fp6/8Gv0sI5ZEyQCobVHqgQRQmCTAdKMGM70D8PwVzPl5ZeJ3LCQ7LgEiqJiCGgayHKWyjj+lziK30aP5ex15fTCTMCzhujlXfDVvIpHWHn62tuJqRrGecvKgfpoLlm0Cy0pHmdld4qirPS45TvCoiN4ZvqLIbGiyxhuqNjFBJOXARMWYbV01rxCQZRgUSgUB5yB41OZ+/FmbPgpTFwAAvoM/AoAqU/H8HjR9qkrdONZmdx4ViaFRdXERDV01NSQGEbzfhkANevWUfbJJ5i7dKH3/6bx+q5d5Mz5kaRTTsJ5a+8Du8BOjIbWwOn215+/YPHrb9WegwW9Uhlb7Wmmd9uo27ZpcR6aRnh4OHmV23n3359x6fXnttyhDdSJlet1Bw9NCf5Oey75Cc3cOHuyYUgyekZTlJtHldtPuP3AhaPX+ex0RLAA6FiIN6KxyWhwVlG5YSEAXYoKkIFqXGFOqqP89N2xk0G7NvNJNxeaX/J26jnEeYo4sXA6AMm9jwIpOW/ZrAbj+6tchFds4ZiY+cxKv4v5BZWsfv4NJsXFsNGyBRxw6rob6VLRmwEj3yUxcWynFyugBItCoTgIOGIK6XXGDURtPJ/NtbXlRK3jpqb7+HH6WHRrTShbZ7BBQ6+GvV+nnAdawM+saQ8gAhqD+/2H6L7jQ618OTnsvvIqEIKub7+F7nBg79ePHv36HbxFdlJ0oeHbK2lbVUm974/WLQpjVxkxpuj9usYuXcdvav3xMfb40Xz9RRHbc9cHt0I66OBqGAY3zNsc+vnBsb0anPeXeXjqL7+gS4FPB6tfYqutf6QjcLl8B1SwUCeeO7ieYLfg/RPeDGzjpuKeGxQhkdUeYlxuHHvqf4db3PGUCjNl5ijKzFFQOAMAf7gkPWtrqN1OdzorhZMykx0yxiN0QXoR7DDsbDZiKTQXMyQ/nvSaqwirCW6F9TvlQmJjxndoHYcaJVgUCsUBJyzOjVbgJaH/e+R/8zTlMWvIzuqL7krBvLgrsZe8DYDFexKalsTeeUXrEEILHQuUlxHuL0KjjMKEZVTlrCa673iklBQ88ywlb70FUhJ/+21Y0tL4I6MJDWOvqJ0Tz7uWJTOm4awAY1cZAHtKttNzP67h3+dBvWD3AnZm7SQlOoXuid1JjU5FExr9h/VizfJebNqzilCa2PZQ2z6ruJqvA24AVg3p3UD4CECz6ITXhrnXpDmwOE2Yw8xUV3hJ6RpBYmwz24BtMRU11c1XE7x2wbpWWjY7ANisUA2yxo8p5kxmH1dDcnYWeo2LqKpqHN4K3LqZr3uMZbVuI6znM4QDEgs/RpzCmI3LYekcztM3YA47C01zUGnyUxZWX3TSPSKO3YsKg5cUsCijP9cXxnD00J7YekZjz4xBc3TuRIh7owSLQqE44CQkjSJsVx/CwjOpiF1Bbu4JVOaNA6DXmAdD7byW7+lhOob0ce+2aVxX3gYK15+CZ8tWCta8RNnHnxAoLUWLiiLt3//GMWTwQVnPkYRGY6fb0++4j2VLfqaqKJcBHy8mOjGxmd5to7vPR40/aAHwumt485M3SXWlspnNzGY2Xt0LkUHLiK3MBgKy9+ST2i2pQ9dLi3WS6JF0kxqJ0Y39b4TDREmcCUu5n7vvGdXECE0jpZvtS7/mqT99WZt8rXn5srcBUKttpecuRz4YC4hgteU6x2ShNTwmBdLnQRrBe/aJ7WTy/XakZT5I8IsA7uQk8pOTqO4/hBOW/wP3JB+bFgwkYs0ubl2/lf/WKkyBlz/99hlHb5ZkR4Wx4PgBmI1tpFdFoTuz+ImROLDyZaqPuO3VjKt1R9/gEMzb42fi7ZMxh3c83Pxwsl+C5amnnuLee+/llltu4cUXXwTguuuu4+effyYnJ4ewsDDGjBnDP/7xD/r27dvsOFJKHnzwQV5//XXKyso45phjePXVV+nVq1ezfRQKRecmLn4iWVnv06MHVBBHWPIqonvObdRum38+CXkLcCSNaXXMwnVfg4Cq73/Et0kDs5mYyy8n/s6/oukdrwL9e0KjtqDhXgzsPZLu6b3YsX4B+vsz8bmKqMpai/R7MPwejIAP6fMi8WPIALpmDfpnCA2EjhAiaPHSNITQ8VQWkxuTxD8evJ8aCalawwyo5oAZd8CNSTNR6iwDn6RSlAPtFSy1ociaICUgWOyQ5BS7SImtDx+eWKIRlVOOFmkNlpau46HI4HeTHZxxcM0sCItvOLy1J96oamKH1Ao4rTZ0et8gq9raQsVVRawoXo1FWLg+fyjW1L54UpMR0giGkhsSpL822skIfhkGnq0ltYqnBlNUCVtr0ulmcpKY1JNApZdqi48NRdsASM5awe6wY3hAXAzHwJ+3/YNET28u+S0Sv+dLIqtKGLJdIgCzVyNs+1r84Xt49thVnLbjHByeYP4Ut+ZgXGG9taWfS9JvuxfftjLMQzoWGXW46bBgWbJkCa+99hqDBjX03B8+fDgXXXQRXbt2paSkhIceeojJkyezY8cO9Gb+oDz99NO8/PLLvPPOO2RkZHD//fczZcoU1q9ff9hrFygUio6RED+FnTv/ReKxD3FS/91kZf9GaTNtAzWFrY5XuPwrdlS/ga3YQcopf8F572DsRx2lhMo+aGgY+yR6+3DBBSR7lwV/eAbgXxRv/leHr5E8JYzCpVOpCVgwIQkYAaSmY7FDhcmNrdLGGVPPYHS/0Xw8axqP776PG0w3d3xRwAsDunHGpp1cv2gLn0wagN0cfHwNcNVuHZb4MR8V26if7HoMYvvPyP/dirjwgwbnRMREYkd4uPbSs1u8tt9fyZy5Q+gOZJdYCay5mBlxXqiEPw87n8ReraSs35pL4X82ITSd5NtHwhNP0Ds5hmOuPotyVzn/mf8fhHMrays8bI7YTITZxNQZWUyfeBdx1msIWMEpIanvBkpjtvHnhMsot4ZxWfa7mGSArplbeaZrDQsiC7ghYCet2uCLVDMnFPjZkSo4+5KRSE+A3CcWI9qRfbqz0SHBUlVVxUUXXcTrr7/OY4891uDctddeG3qdnp7OY489xuDBg9m5cyc9evTYdyiklLz44ov8/e9/5/TTTwfg3XffJTExka+//poLLrigI1NUKBSHmbCwTOz2dEqq15A59GkiM85l0aITMTRJQA9+Eh4YdQW6JYqwro2L4bmLdlK69mcqy9ZTWrqAqrRCLJV2hp00DXtCRqP2iiAaAp8eoMpTTMDwE5B+DG8OJQErEckX4dxTSldLMppuQegWhGZG081ougUpDITUghYaKYNWg1rrgQxZDQJsKHmdYf1mM/W8YLG98pJiXn7xRfyVAcJ6huGv9BNTW8362AFHo+8089lv3/D3s25v+0KM2lwttVTPmsV9O7KY5vBy/5JvufXGP5MaF0u1XcPqMUg/vRunTAr+v/BmZePJthLexYPY/jMANfNn4Lhw34u0zX+luGJD6PX/lj7DWZbVoa6vfvBfBnbpydnXXNxsf1N8JELTMTzFBLxeADSTCSklx312HAERCIZwRQXbl4V7WdZnHfd9UoQrSeDM14nqMZNucYsJT3WhbfMxquA3opNiCThKSRhSBMC/ooLP38WxkGwxEeaXRMfHIX0GrsV5wRVbj1yB3yHBcuONN3LyySczceLERoJlb1wuF2+99RYZGRmkNeMIt2PHDvLy8pg4cWLoWGRkJCNHjmThwoVNChaPx4PHUx+WV1HR9kqiCoXi0CCEICnxNHbveZM+gUfwlJURWTIUn78UQ3iQwPa8b4nWRhDZ3YXJERHqu/GbG8h2/Bgsp+sEq9tB18A5dD/nQXRL23OI/BHpGlnFyV1LWDS/Pn9JFyBPi2fKgPtgwP5fY+2XnyBFTejnyJhYxowYzq/LV2Ls9BPoEqBPah8AUuOTiPDGUOovadc1ZMDAn18NgLu8klk/vAlAnYfK1z915y9/+hMBs6CmfzSnTan/QKxHRVKwKoKqHC+GT2D4NNzlJppyMmhL5FJ8VH0ytVhRwq++7pxsrRcx1SUtr827I5gQ0ZLsx1/77DKZTHgNb1Cs7EWyN45BcblEo6MJE/0rNJxn3ELm1hwSdnlZGRbBW1MH0vu4qwGYM+ds/IHgLtTzn9zMbk8CAanjDGiEpd5A34WF5C4MWjCFRcMUfeTuWrRbsHz88ccsX76cJUuWNNvm//7v/7jrrrtwuVz06dOHGTNmYLE07eSTlxdUfYn7OIElJiaGzu3Lk08+ycMPP9zeqSsUikNMUtJp7Nj5MvN+PAq/uRotTGCudCI0Dc2vI6UkK+4HsmdPR3PraH4NizcCV3wR9qIo+h39AmFpQzBbIlq/mAKAkTKMSo9OoMtFaMKEEDq6MHFs0oRW+1aWFbF701o0k4amCTyuPCwOb9AhdS+HUre7iIDXYNn33wQtMYZByY4doXEG96t3FQgEDKpMZURq4eQuysMWYyW6V9vCqrWI4HOjuKQsdMx33ImY5/zQsPzAPppDczjwVpjxVphJevQRXHN/JeWiP7Xpmk3OQzPzdJ6NflY/97ifZVduN/wR0UghOPnEixh4+sRm+0rDwJcfFAyOEelUlQerLq8vLiLT42/UPsYfSb/FF+Iu7YnZW4knZzWBH//M+hP/gVu3E7vsX8gz6u+f33U5JdX/oIsrgtwyDT3SgT5yHHqVG09WDSLDSWzPLpjjHdiHxHe8dlInoF2CZc+ePdxyyy3MmDGjRd+Siy66iEmTJpGbm8uzzz7Leeedx/z58w+YP8q9997L7bfXmxYrKiqateAoFIrDh8ORganajt9RTXLJeHpOegpLZEPHx9Ktc8ld9iY+o5JAwI2HfBJKj6bPqf/EEtb5k1l1Nmwa+Fxmxg16sPXG+/DLhz+QvboLhBLPxdL7rBvRTN4G7ZxJULo1gtnvvN7geE0szB1WTESxBM4la2sJd393H74oD+Hbqgks3YIL0K4fRGR6ZItzEWYN3WmmpKyGq5btZFLtce+K3/BGRNOve9CiImQTPrKaRvfvv0d6Pdj69iX63P1PWnffyJe5cd6t/DLEwNEvi/c2X0/BRI1BUye12C/77g9ATwfAFBuJVhtdtaO0jGeefoZRjlH8lvhbqP06xzZGeMJILV7L4DWvBg9uhj7PbSMrdhdiVxbTvv+Wsh98ZHTpS2x8NOvWTmTwyefA9/eglZdgmvMDXo+Hr5nOaef+jcij0/d7/Z2BdgmWZcuWUVBQwLBh9Wm1A4EAc+fO5ZVXXsHj8aDrOpGRkURGRtKrVy9GjRpFdHQ0X331FRde2GgDkaSkoNd4fn4+ycnJoeP5+fkMGTKkyXlYrdZg2WuFQtHp6fJlb8wpqXR77OUmz0f3HEd0z3GHeFa/X0rSNrfeqBkCPokjNp8Trx3FF0/WWkyyH6D/hB6ArPVtMfB5anCH6YwYGYHQNISm8b/nn6SbTyNWuni79EuurLiJt6Z9yerYeVxScCqnl03EIOiqkfX2eiIfapxKf2/yHFXMjTTxt982Uh4RxoSn32VIt5hG7YQE2YTVwNq9dT8n0UIY876M7HoUR0VGkxaexjm9r8WxXQPaUE1aT0d6sog6NRPH4F74Nm7EsW0t3foOJLx7D2pquhCbYyXHvRl7lYckV1eSsr5j8NblDYbJ/utPaJZgdFRyZA+KylezOWcFZAdX8ON/96CZ0rA4E7E6Yug1IpmIOBvdBgW3swp2VeCIsBD2R9kSmjBhAmvWrGlw7IorrqBv377cfffdTUYBSRksbLW3z8neZGRkkJSUxC+//BISKBUVFSxatIg///nP7ZmeQqHohERkjqHkvfdxX7IJW58+h3s6v3vibjNj8Qg883Owxqa0u79mMkjqloEjfBnVlTFsXpTIgLEpJPdsORJGN5kwjAAXdj+Xp7JepbKmgosGVPJ5ts6S2N48PzwslBn2jB0e7szexfJdqzGbdOwmO2ZhxeP3UOIuYeaWOfx8TH/8tiQmuwS3D+nKwCbECoCzKoB3d3W71xmijVskVnMEb54RDMt3u2soYmmrasdfHvTzsXSxEH5CMEeQ4fOie90M7N6DzAuDjrpnA1UV5bz/2AO4SrdRbAtauIqdNkrC7MRGDyDcUh/KPXbiGMYnj2fmD/NxVbgp3eUntU8iun4t0SlOVv+Sxdp5YLbprJ2/EpNZoyQnKK6u/+d49CM0UqhdgiU8PJwBAxp6bDmdTmJjYxkwYADbt2/nk08+YfLkycTHx5OVlcVTTz2F3W7npJNOCvXp27cvTz75JGeeeSZCCG699VYee+wxevXqFQprTklJ4Ywzzjggi1QoFIePuJtuonL2bAr+8Q+6vvnm4Z7O7x6LJ/gUDVSXQwcESx3n3jeVd+5ZDMD3/7eQq55veVulxuRnt6MUf3awLo5fM3hq+6uMX/sqP8cECNuUg1+A1AXfjE5gwYxzkMLd5FgOGY6hH003PY+3Tm8cQbYv5sKO10Y6GB4dxe99TeXMHegRsQh7BubUqNA5o/bDuzA3zDAbFhHJ9U+/hL/azUtXnMP3g+udiLeRh8m1hS7OWrdhTRKTEMk5l51EU6QPjKM010XAL6ku9+DzGgT8BuUFNQQCxh9DsLSGzWbj119/5cUXX6S0tJTExETGjRvHggULSEioT1SzadMmymsdj4CQg+61115LWVkZxx57LNOnT1c5WBSK3wGa1UrUWWdT8PzzSMPocME4RduoutOOhyL6pe1fHaWwqDBu/PcJ/OeWLzCMfb1EGrM4PZ+1CYWIQDaRbgvRYbFIZwK7zD5uKAj+Lf/B7mWtNYB1y1p62HvyzMlPIQOSal8NXunBarYRY4smKT6OfrOnY9NbLngJ4ArTMTJb9odpjtoShu3vWHs/TO6m+5Z/sxxLz0kYrmzwZeMceVzoXF1Ys25uOhDF5LBx+hU3kLVqOXpaGtawMBZ+9gHzi76hd9Q4LIUBMrWWrV1pfWNI69vQIrVxYS6/vLPhiBUrcAAEy+zZs0OvU1JS+P7771vtI2XD//xCCB555BEeeeSR/Z2OQqHohLg3bMDaq5cSK4eActGDUhnHunXfYEgDI2BgyADSqE3wZhgEAsG8KoYRwOs12LPCTlpqGFXFeqPnt66LhhE5zaA7bST4Ivnf+d9jsdkxmc28dtGvvLL5e6iNgA6378Qatxpz9DzePHsu0eFRzY5XqXehVLYeCi01QgKiI6wuXM1/VhU0WLdABLP7ItCEVv+zEGhoiGqD48ggdaGDLMty0EUwC7AuELrAMnEM7ARf3mLsV02iZPNKxJY1oEHJ+mD9oR1bNhCYF4PJYsFkNmOyWNEtFkxmDUefWPr2m4qmmdB0E92PegxN01n2/ULWbv+U7p7zqSr1UFduSwgRTEpcm5JXaMG4rtBrAT5PACFA0/4gUUIKhULREWpWriRs/PjDPY0/BPN29wdg3Z4V7epXOm8wZl8ySZlZDY4H6+G0LliEFFiFGUd4fQi6pulERNtx1SYyLk6eziO9u3LuxOVoeuuPn1yjab+VBvNrKpV+Oyh2F/HPlZ+1q48uNY7jleAPc+odb2VoKkF/E6Mol/JbGybL2xMTDmkJrF2ygLVLFjQaO21cLrH9ypq8rtYNBlwq+OmNVcjAtnbNGcBiN/1xwpoVCoWiI1gy0nGvX3+4p/GHIMZkpsTvY/iksSAEQuhIoaFpGnrtd4vJzJD0dKwWM9k7C3n/k3cZeUYGoycMaTSeNASa1rpgiarw0W1TOT+/+FcQWu2DUdDVLPD1NcDv5i6jB6btTn7976NBi4SmB+v36IKMUZNJ6z08NJ7dKKaXuRJoPKcG8xMCITuuWDJjM7nrpKsRdTWYZDAeypBG8LsR/B6QgeDPGHg8NZzCX7hCP4WLj7kOaRjgN5ABA2nIYNK74gIcU65GGgbSCASTBMsA+uoVsOw3Erv3ZNjUU/H5fAR8XgI+H36fj5Ka94Ay7MYUoqJGACLYnwA1ni1U8BVTru2NyRQfzAQs64JbaPA6mJl473OS8LhmqlYfISjBolAoDjoRU08k929/I1BWhh4Vdbin87vm5+QMhu3ZzLIZv7bYbuX4idw6/lis1iqA0PZCHUWFC1m15mISjuqPp0JSmDOI+JRBTYwUZPwSF5nrawiI74LjQW1l47axevAPpH1SXxxTk42TqjVLB/WKQBBrj2NQfPPragqvz0NAGJiincR279pMq6Yj4mRyMquW/Uaf0WPJPK5xMr/y4pEsnH8ahP1IZf5MBvT7L126HwtAUdFMVq3+itS+sVitjesm/d5RgkWhUBx0rD2DEQ/e3buxK8FyUImIiOLLoeN4sV83NE2gAZoQSCEwEBgSZnz0Pjk7d/Hp0jBKc4N+IotX5LOrZGPQQmCAybeYmBRwJm4kLDnA9g2ftyhYEt3heBJ1hsypFx1SBnO3SBm0UGDIWn8aAyPgD31fcMXpuGvK+eCHPwe3VaTEo02mUFp4c/GP+LQqRHgcZs2EWdMx62YsmgmzZsZr2oapwMSs7xpHColai5IwBJZKnXBLeO2J4D8mw4QWaNStVXQtmMLDaINvz77UbYU1588VGZvBhKlLWfvbfymxP8+G7ZfRpXtw+ydUhfsI3tbZH5RgUSgUBx3Plq0AWDJU0cKDTWx1JUUxiYzt3g2zqek/8d+FRxK2cwvrd24JHpAgt3so2pwTamONiiQmBUTtE3393F/4aV4kk0+aQL9+vYkI27emU2MzR53jKgJ09GBtqCZw+D0U4uWlvF9DRQBMcX0oMo/hgUodv5YIlfv2koCX60278AVgzpKWfTqEoRNbMKa2zEAQDROxFe1PQqrVCpa2OCM37hu8vmE039dssRIRm0pJ/j6WL9nhuKbfBUqwKBSKg44WFgZA/mOPE3HKyTjHjEE0kWhSsf/k5uzE6NqHN+b/xvXHHdtkm/uvu4a8ikrMukZWpYdrXl1CYo8IhvWI45j0aCb3iMftdjNjWT6Gbwl43ORqw7BumMu89bP4WbPi7jaEUyaOJ/zvd+Hr3RNLYTE4nU1er+STn/FsLyZsTF/Cjxvc6Hw6VrprGpdcsbThCSmp+PZSwpdNo+qvqzF0K96AB2/Aiy/gxRvw8vliL/ExVs4587ZG40ppEAgE2L58Iz8snsGp13YnvltSrXesZOvzcymK97X7HgshQLYsOprtW/v/XrbSd2d+vbNucd5GYpP6Uu/8/MeMtlOCRaFQHHTCJ04g7qa/UD5tGuXffIMpKYn4W24h6swzDvfUfnecl7+buUCJt/kHcaTNSqQtaFmIcfrwWMzsznexO9/FjxvzOPeuLkQ6LVw8+e76TmdBeXkFC5dvZNuShZSvms/Kl+cy3nAiFi9FWszow4c3ulbRW99Rs8EJMp7yHyoo//ELYi8ehj2z3tomAwbC1ITdQAhMfU5HLJuG3P4DkYOub9TEZv4Qu91CdFzzBTKLI4Ln7OEWHLH1jqf7k5JESDDaED3VqF+dyaQFR+G9U3/4SroQFtUleLwuc4zaElIoFIqDg9B14m+8kbgbbsC9di0lb71N7r334tmyhYTbbm2U9VPRcVb2CvqZJNiaTky2L1E2MxsemIzbMDj7w2Vk5TXaewkRGRnB1OOPhuOPxuO5nndfehNnyQBKrNkMefiCUDu/u4YAGuXTf8OzzoowF5PywMkUvvIl3qIulLy/lC5P7LU9aBigN60epLsMAOFouhCmqSaCrG2CeTNnMmb8eLQmfEOKsvMREqLT4hudkx189gvA6EB0Up3vSkvWmZ++74PJDr7yRKaeU+8TVC9ylGBRKBSKg4oQAvvAgaQ89yz2wYPIf/oZjGoXyQ89dLin9rshKioOs9/PVePHtLmP3axjR8eki5Y++DfAarVyxmWX4HlhBZE1Mfhrqpn31GOsXb+KHUlpfHDW9RAZyQK5hW4PnI5mt5B455/Yc+v7SIsVw+9Hq/WxkVXFCJr2fvUv+zcei4Yz49Qmz4/09OFT6yJ+njuX6Qtmkjkqk/NPOD/kGOut9rB84ypS7PGYG4m4/XvwS9l+j906QdWU/8uCmVdSwxx81Va8VWaOnzKt4fVqLTpC/DG3U5VgUSgUhxwhBDGXXYYvJ4fKGT8f7un8vhACU8DfoW0DTdDiVsXMD9ZilHtqo38Ar0EmIDUbf7rjX1SIOCq7nsGu3r2D2Wc1Qdf7p6Lb9xIKmgm0JLLv/gXNWogwS4zYqUhtZYNr1eTOo2LpsyTu2kLJyNOJ0Zt2jo23afyU8hPH5B9DUk0Sm+dt5u9L7uOMfieSk53DrqJsyg0XZ51+drvvR0sIKTpkYdGa8WHZsv4NXP65rH6jvqRCZuZSwqKm1jcKiRxlYVEoFIpDih4Ti1G9H5V2FY2oS9jWETSteQtLSUk1vdeUUiIknqDPKUJAgSa5wKjCG5EZamvaUYW/Rzh3SBumqPAG4ziGxeLelI0QEsMTDV4T5j7noTGsQTvjo/NIrHBRHGMjZkrzRTMFgi+5h7OSngIJIwtGklqdyg8rZhGpOUkMi+W4/seS2i+9ib4dJ6jtOuDDErKwNLzRq2Z+ApaG92rZzBfJ6H88mmat7VNnYVFOtwqFQnFIMSUmECgrw19aiik6+nBP53fB/jyEdSEaPUjrMMqDRftk7yiOuqI+H8t9n6/Eu7SqQVvvgGjQNbwleUDDIoyxF09qNHbxk29jBBpaUHSvj7LUbkRf/htCa+FRJcGka6y5ZA279+zgp5XfkhHRgzGDj8Me1XTUUh15VdvZuGItq/Nm1Qdl11mP9grTrr8nteckDCyJYJttM0+89EJQudVatIIpXmpFo9irpk9dnZ9qFzqwc90a9C8+QtN0hKax61czlsg4HPFeqguDFilTRC5btz2D09EDhEZ+Xt0WkRIsCoVCcUgJO+YYNKeTwpdfJvnBBw/3dH4XCE102JFU00SzWWOFKfiQ9DobPjYGp0YxcGkJKwiw3eyh2sgjc/sqLNsDXDCljdsw+2xfVa57i3C3l5qUIWimffO9NOocUmld0zK4Ou2mtl0T2Fg8D7dRSU1BoAWl1/SJwa4oCqIlnpw1tVl9a2/c3rlSQvny63pJpGFg100U5WRRlZ8bTP1vGIDAW27FC5x936NI6SO78layst6ttawEB7Fak9C0P6aTuhIsCoXisGGKj8cxahTeHTsP91R+R3TcxtKShUWzBX0vPGENH5bnjUrn260V3LS2HMNn4U3bUjDgzptuxxnbfKhxI/ZSWYGdszEERE3+T9v6dXDJhjQYNuxEjv/rn9vd96mLzqRo6Mm8cd3V7epX5PUzYP5a3hqQzonxUS22zaC+OKKsEz+oLSGFQqE4LHg2byb8hBMO9zR+NwhNIDvqwyKa97ltyYn3lIsH4fEFsJg0hr9ZRNfkLu0TK/sgAzX4TRoWk60NjTtertmQAXS9Y9YKzTAYHNHyllNLiHb+jvbHN+n3wh9TpikUik6D9Hgo+/xz9vz5BrxZWYd7Okc8Qmj7uSXUzMO/NqV8c9rAatYRQnDqVWcz+KRR7bvwPvP1+yuav1BTnffDwqJ10FohDIOZq/I55rV5vL8up8W2dVarovKKUP2hP2jut/1CWVgUCsVhJeWpJyn//nvKP/8C5zHHEHPxRYd7Skc2+/Eg1FvyYanTKx0I5W0Tew1bUb6KttpnzK4Y5Kbw1hvW4vEUYTZF1RYhlB0K/5ZSoiHxVvrI3lHOC74tXNw/pUGbPVu2seDNd/Bs2kiVxcL/XXglRREx3KrXAPY/uK2kYyjBolAoDivOMWNwjhlDxfc/IH3tr+uiaEiguAR/VArXfP4DIBG1dXOQEiGN4GsjWEXZkBAAArVp29ZWOJA+g/PveJNKfzVFCXZ8uo5EYAvofE437Iu3M3/16vrKwQRjZ6TPRXjARxc96CRbv4Mha6NoQkWSQ191bTzl0ZjIxveP45GalS4BEwhY+v2lDdYm0EBqCFH3pRPHnxAeM3nPLd1LrO1ldZH1Tq/rhp4fGqv3kjeQUmL42h+aXBdefMrgVAp84RRmVXL516u4fXQGgxIj8ObmUnXqKexd2/qNMy+CCMj3loDepd3XVCjBolAoOgmW1FS8O3Yc7mkc8fT+5UcGGTq77XZkKLyW4GshkEIDLehBoQG6lOhSogGp5hqqrH5Mbj/RpZVURwYIxIbX6g0/X4siejg9mPQ6LxlRqz0EZeXFFOoG3ay22tBfGSoyyN7BMpJgUjkJkmDeFyHdmEQuAWIQhg9D60ZpdBUBo4p6hSMBI5jtVQa/SwzKk+cTVjgUUVab3yT0Ty17aRdHcSbVseuD7SqCYdoY7bcY1SV903WN60Zm8M9ftjJ7STazl2RzyeSePDQ0CW9UNJayUgC2p6WSHZ8EQFy0gArQ1J5Qu1GCRaFQdApsmZm4168/3NM44hmamswLLz5Gv40bOjxGSd4u8sdPpfjEqzn2wivb1Of5z89kVsVWzr5yTbuvV/z0OwTcvbDd/UjomANoix0i62/zMHdxknjj0FbbyrtOA+2u4GtfISDR7e13ujUCwZT8mq5zzeA0rhmcxu5KN+e+v4T3ftjCz+vzuezVj5ldXc3c7DL0LBdaoZvr+xZyca/J/HPRRixKsLQb5XSrUCg6Bbb+/fFs2oT0eg/3VI5smkn93h5C2Vj3Y4z2UFPSHU91esc6S4lopnDivqQ+fQ0xFyZj7+ch9dkzg9taHRAOdYJF36vQYtdwG3OvOYaTj08nv7Capz5Zw2//24ZleTF6gRs9p5oHBp+GUWvv0ZVeaTfKwqJQKDoFjqNGIH0+qpctwzl69OGezhGLMNUKFr8fYWm9YrNhGEy77goqqipCWV6lNKB7MilV7SmbIDoYXLyfSPDlutrc3DG4J47BPUM/d8Tp1h+o2xJqWITQatL415T+1Ezoy087isit8pASbuPtpatZtsqN2xcgUHuXdGVhaTdKsCgUik6BtVcvhNWKZ/NmJVj2A1FXAdnrhTYIFqRkW0Ux0VIQ4QwHBAYGezBwhLeWZfbAYI/egeHRgLEd6i/MHdssCEh/KMy4PVS7g1bA9XlVTZ63m3RO75UY+nlJfjrLV26itNqLv/apa1KCpd0owaJQKDoFQtexpKdTvXQp0Zde2qFPvgqgLq9IG51JNV0HKek3+ChG3xcsj1BRVcLrV11KoD3+HftVSbDjthmBC6p9FD78fl0e2OCJvZPR1Dr41v9c//q3Xz9j2ZI5+w7a1MvQ9pGUwS2hNdvLmfxCw76b86tIibQRbjOHdps25lUCMHXBBpzRdkBZWDqCEiwKhaLTEH3xReTd/wCFL75Ewm23Hu7pHJnUJniTAX+buwjA2Mt3qC77a52vRltHORxbQhH6h3hlLzAlgG4CLZjALhRcVD+9+rDqWt8VYeqCwExUSloomqlBlJHcK3hb1pY+DEaIU1GUzri+A/GkxzSYT/e4MCo9PnolhCNr+w9MjWRjtYcBXePArDFJi6Cfsw1ZfBUNUIJFoVB0Guq2gqp/++0wz+TIpSMOs1IIlqxfwYiyMqxRUZhMtYLlEDndNqiM7Df48a2VGN4ApoDEbdOR8XYikpx0CbMRFW4lrmsEmqaxu7iKruZvgh19wa+AV8NtH4H95o/QIuNavGr4n2M5amgZQ669uF2zDfgM/n3TbE48qid9RiW3d7GKDqIEi0Kh6DTUJY6rWbUK786dWNLTD++EjkRCW0Kti43ykhL+++dgcraApoXEjqbVOu62w8Ky/xscwRFcJTUM2ObCZRbkxFkIK/MRv6sae6AYAC+wOFynrIuDARsr8VlS8dS4keH90BJ7IvJX4Qwspvqrf0B4KlpYBLYpVzR9RWFgBNovykRtiI/RgRwuio6jBItCoeg0WDMy6PHzz+w44wxyH3oYx7Ch2IcOJWxsx5wx/5DU1fxp5UHsNQxWTZ4IPepTylsiggnx9TrB0s40/Afi8b0zu5wooOyCnhzfP5hsTRqS4pJqdrs8lBdU41uaR9dtQYfX7T+n4/YWMnjptwB41y+CTyfj2Flf6blq/WyE2YYsy8E06jxsEy8BQBNGW3RdI+rcT4yAEiyHEiVYFApFp8KS2oXI006j9MMPcW/YgPF/r9L17bdxjhp5uKd2RBDaEmol+sXl8RJfVcOQXfms7BaMaCmpqCQmIjxUSfig1Q3aB4FESsGKtXlYvtrOplgTY3vH15/XBHFxTuLinNAtBo5KBcDrDbBt0HZcvfqE2loyR1KdcQPkr0d0Owr7hmcIK/+6/mLz5uKe+Sh+Z1+EvBRfaXn75ysEmiaQysJySFGCRaFQdDqSHrifhL/egbDb2X7KqRQ8+yxdnnsWU1ISmtV6uKfXqVlRtIpuwKKzJuGzmxGGDH7Juu+gGRJhQDRQaasPfX71hvNqnVMFVrRDVlK4wleNqaYn8e9vYV2Exq2DzJjm10XfiL3+rRNRBpoIWoFeiI6leHDfBuM5Lnsy9Npz73+xWoMp8l2xZ6Pv+AFbRD6B6kIIXIy3xtmhOQtNqC2hQ4wSLAqFolOiOYI5QJIefICcu+5m25SpoOuEHT+ehFtuwdqr1+GdYCelKiUagOK+SZjsjmDm2zr/FF0DLfgldJ0yTWMPkbgSwog1+9latIZyTzlju4wFTTBlUtsrZ4v9iBIyRc6giBz+mzkZa5ciTtWNYKFGaiNz6kotSpi+/jEAzLodQ8KVxz0Ifih9+l0cZo3wqHBOOHsi4RHO2nntlTnZXY7pr/NwffE4tvMexvjbEvzYOzRnoQs6kMJFsR8owaJQKDo1zqOPpscP31M5YwaB0lJKP/yI7WecSfLDDxF1zjmHe3qdjuSE7sAsxv3jTWISurar791z72beju/58LKnDs7kmiHMvpMI1vDKmY+32vbH9Y8hgdNSemEYgrfXBY8/URIbfJEP8Q99y52Dwphy8mic1/0Ebx+Dt8bGxvSTyXr7E4469XaciWloclGHRYemCeXDcohRgkWhUHR6NLudyNNOAyDqwgvJf/Qxch98CD02lvDjjz/Ms+uc7I//SVlNXZXkhgQLPgePa7Wl6AQCoYG/rvqy31ebB6Wu/16vm9tikrLNYUYnJfdiefEOHjjhAwA++PUDBqUbfHbZxbj9AXau2sTD7y/gro1hPLJ2Fhcl+CHsdZb4S0jfnk+E5mXx518y6PPPEAzokNMtBIOxDl3YtwKUYFEoFEcYmsVC0kMPEigrI+vmWwg//ngiTjqR8MmTQw6nf2i0jvudFFUGk82N/bT9pRFqnOOpyvg7yb+uw2T4MUs/ugw0+n5+3nTu3PV2g75RBCOMjIciGxyvOOp0ok5+t8ExsY+y0YQkYEg0TeCwmMg8qj8fj8hk3eptvPTOTN7Pj8Fi+Cm1prGctKCDL4JlVXs4GR2P0fYEew3moTLVHnKUYFEoFEccQtfp8vxzlLzzDhUzZpB9621YM/sRfeGF2AcNwnBV48vagy0zE2vPnq0P+LuiLsKn/Z/+o/RuSKlxbtc7ESJo+KhH1nmS1B6Xtclhgz4m31ZGUwU8a8/BBwQk+BD4Ab8U+CW8V2Hlxa4Xc8eud9CQVPc9DYfZiqt6B5V6JZb4ISFBYlv+JaJoS6M5akJg7DUxISR+v6TG7cGQwYR5hmGQlpHM0w9eiGFIpJQs2LCHT3/bSlmNQVmVn+2OZIoMJ27DzYSKpiuEt2alUj4shxYlWBQKxRGJMJuJvfpqYq++murlKyh8+WXyHnyoUcI057ixxN98C/YB/Q/PRA8THdkS0oQZEDx4QvsyvwIs+2kNxW4vFx9/UpPn0+/5Dqgh23YmANlJVrpc8B4AztqvvanY8AMYrSeuc1T7WbsjgX4P/dyGWdbVRrKCBj4hcbgcvHXXvDb0bYxmUlaWQ4kSLAqF4ojHMWwo3d5+C39pKb5duxBWK+bUVFy//krBSy+x85xzsPTogfOYMdgHD8Y+cCDmtLTfpVk/tKbWrANShr4Mw8AX8OH1ezp8XaOFGCEpJWdo83BRXz9na3cnXVoaT+gEfH7crpJgRWUZtJwYbj8BD2QV7kRDcFzpLMojujJ46Dg0rdanRgQtMXU+N8HXjY+v/Po7YjMHMXLK1AbXbvJ/xT4HhRAk94xsqqXiIKEEi0Kh+N1gio7GFB0d+jnipJMInzyZqtmzqZozh6qZsyh9N/ipXo+MxDZwILaBA7APHIhtwABM8fFHvIhpS+K4v3zyFxa6FmIII/QVQlqa7dcShmy66HL52m+I/PxSXqwd9ruEAdj65jG679stjjd7cyrbCiLhl0sbHI8DTiGVT6b/BYBUIKWHjVsumtz+Sc/7jIR4FxmDWq45pOgcKMGiUCh+1wiTifCJEwmfOBEAf2kp7jVrqFmzBveatZR9+hnFr/4bAD0mBmvv3tj69Mbarx+2fv2wpKaiOTuWXKyzsti1GDNmTutyGmZhxqSZMGtmvlpVRJErjOyiPWiajiY04iLi0XW91TENmrZMVGyYzt52iEkFG1jpncKm4nkkZf2dnLRT8PgNIhK60e+489D1oOCq8UeSFBWgx2mTECKYxE4IQU3AR67Hi90Wj9/wgxCMOfrEDt0HaRiNnHgVnRclWBQKxR8KU3Q0YePGETZuHBDcrvDn5lKzdi2ezVvwbN5M5ezZlLxTH51iSknGlpmJc8wY7AMHYe3TG83SMUvEwaflB/Crs1+lRq/h1u63ctXYqxqcs1W+QEbYK2xc/WroWFbNaCaOfByoFw11hNnCiXAE6w8ZUjZ55ZSz/sm6zHNZ+dsXHFU4lxL7EHqVziWq9Ad0IUkuX4lP6pg3Bli6+C3SLnuDxORUNM1EwBdg1Mm3d/hOtIaUErEfUVWKQ4sSLAqF4g+NEAJzSgrmlBSYXL+tEKiqwrNpE77sbDybN1O9ciX5TzwJfj+Yzdj69cMxdCjOY8bgPOYYRBusEIeS4poiDFc4hjSCPiDA6m2r+b9d/0cfow8nZpxKflYxgYBBIBDACEiSKAx2jnkGaQQIlNxHqn0hG1ef0OQ1PAELx41ditPmbNbCousmMjOP54LtkVQlXcmOk4fjDxgEDIkkQG5OFl3SMlg/5xN6zLkT66tD+axkEAUlFpKiD+4jSkpZX91a0elRgkWhUCiaQA8LwzF8OAwfHjpmeDx4Nm6kZs1aalaupHLGDEreeQdLt24kP/UkjqFDD+OMg5R6SokCrvnpGsqdTVsPhq87ka8WrW10PKqHCdtQjYlDzgJgV8Fwtuasrj1rNIjjLSr6iTj9F9xeV61gkU36sACsL3ZR6NQ4zx4GgEnXQAfQSevWHYDM4y+grP9YPvrHvZQVliCEZOJf/taBO9AOpHHE+yz9kVCCRaFQKNqIZrUGo4wGD4aLg3V2alavJv+JJ9lz1dX0nDUTPfLwRo5E2YJOxyeln4QeF1sbNSOCvhoS/Pl+Ag4Nt1HOqMnd0XSBpmnoukZRgZW97STdErrTLaF7k9f5fokXKn9Bq33gGy0kq82p9oAQjIgJa3nuCV0474FX+M+1f0JKweIsL1My230L2ow0pEo2eAShBItCoVDsB/ZBg+jywvNsPf4EKr7/nugLLzys89G14NbU5f0vJ6Vb00/7p9e9jy9QwzFTBzc4vmDmm9TQeu4TqI9C0vXgY8QAmnv07yiqBsDlbj2rbHhkBKNvf5yFz9/H1rXrmTL5uDbNpyNIaSiX2yMIJVgUCoViPzEnJxN5+ukUPPMs4RMnYoqPP2xzqYt6CbSUcl7SpDnEw28A7Ml6L9RQSlm7baIF+xEUKkbNfAAWblqOSbey3RYG6Py4Z3GjcZdVBgA787YUYqn07TPfxqyfs5hkoGTtYn78MRNEsOKAQKDV5lJBgF77esiwQTgjIppfb3O3QaIsLEcQSrAoFArFASDxb/dS8cMPlE/7H7FXXXnY5hE+fwcABe8vIu3+Qe3qK2qOA/vHbN78UKttHYA3YObGT10Y0g2TnSAEl21tPnrq142FzF+a2+rYcR4LFwIOVyFr33ym1fYL+h/HnQ/c2Wq7fZHKh+WIQgkWhUKhOADokZGETTiBiu++O6yCJTI8mXLAXmJtf2fPELbP6cNZd3cjaPuQBDd6JBIDpEQIHSn9SCnJq7LzTe8YNAEBJAGrCau5sQDYmb+dvJ1PoI29h54pR4eON5WMt+6QNKbi8FdhM+u1GXmDodOGDNYSklISkJLpzz+KvTiHTQt/DUb9yNqKR7VtQt9hr/MSJPhqalSU0BGEEiwKhUJxgHAefTR5P80gUFGB3oEtigNBeU2wXo7b2nSYdW5RIYZbNJt/3udKIDa2bX4jbd358peXYbXuITIljBG92rNdlthqi2m2KCLytvDti/9ox7i1CEFUYlL7+ykOC0qwKBQKxQEibPx4tGefI++hh0l55unDkpvFM9KO9X9gu7hr6FhVtYuNO3bQr0cP3ntiDuHVyVSmNLE104Z6iVuXFZC/fTcl2asZccqxJPfs3WqfOn8aXTvwj5w1mWcxJNHB/af2RwiCye2oFWSh18H6QdRFTAnRKAmeovOjBItCoVAcIMzJySQ/+gjZd95FwFVFl+eeQw9rOZT3QGNoQadYpzNo4fH4vLx1xwI0qTPDsR6z14YrtpAxJ/ZpZoSmVct3Lz/DxvlzsEXfjrv0eQA2L/yS2z+a1qrjqv8gChaEhrTYsDocB35sRadCbd4pFArFASTipJNIe+01apavYNeFF+IvLT2k1w8YwbBkrTa8+b83zUOTOg4NoqvjsPvDcBbHs+aNChasWt6wcwsWFq+7BgC/eylC22u7qw1WCqNWsJgOgmARiLYYhhS/A5RgUSgUigNM2LHHkP7Rh3i2bafql18O6bXr0vDX5WOJ7C+wCZgUYeaUKDPjw02E1f7lr/JXNegraV5/nHrrPUTEJ+CvmYs0AggtFlMb6yntKqoAoMzdfAXp/aEp513F7w+1JaRQKBQHAWvPntgHD6bsiy+JPPvsQ+YvUewqIgJYt3QpuXuK6DfcTLa+HXZnUGYYROkaKWYNyyUOxg07qkHfwvJlbIuO5MMVS0FKDOoibCQGBpbLU4gxkjAMPxKJEIm8seQeZG07s8dEn6KepDliARlSEl0Ks7HJ49m6qZgZS9fUX3Cv7Li9RnWhW8+Ydq9XuaH8cVCCRaFQKA4ScTfcwJ5rriHvoYdJevCBQ5KkzMgLZpXtMzcWzQogSSSDKr2GzMcnsuNv80ntG02/EYMb9V1vcfFjz2/5cXWjU60ikJxacjyT8nsjhZ+9w5C6EoNkADFSB+q3yOoMIxYEa/Or6XbHyA5cd++RFL9nlGBRKBSKg0TY2GNJeuRh8h54EMdRRxF5yskH/Zqj4o6mkGmYruiKiI+sNXRIUsIj0HQt+IBvxixhcmRgLl/A3It+BLTaOkQamtAQaCAEmtARaGha3fn6sWZ9+Q2eAi89npzQrjnPffBXRKDj20VqS+iPgRIsCoVCcRCJPu88yj77nKo5cw6JYCnOLwCgdEUB/S8b0K6+hhFAkzph1tjWr7NsF2Xf7mBX36DFREqJlu3FJKPaPWcpaLbSc6uoPaE/DPtln3zqqacQQnDrrbcCUFJSwk033USfPn2w2+107dqVm2++mfLy8hbHufzyy0Ox8XVfU6dO3Z+pKRQKRafBOXo0VXPmEKisPOjX8vi9APhL3c22aS65q18G0Nr4WMhfsA1rjU7aqnBSVjtIWeMkqSSKrPACDKN91hJDiGC55w6iLCx/DDpsYVmyZAmvvfYagwbV16rIyckhJyeHZ599lszMTHbt2sX1119PTk4On3/+eYvjTZ06lbfeeiv0s9XagbTSCoVC0QmJvuhPFP/nP1R8++1Br+ackpJMIZB5wZgmzwtksJJgExhG2wVLSU8vEdlmuj00Fotl//5eSwGigztCwQICSrH8EeiQYKmqquKiiy7i9ddf57HHHgsdHzBgAF988UXo5x49evD4449z8cUX4/f7MZmav5zVaiUpSaVIVigUvz8qa0ObC1/5F54tW4PbGJpGMAmrVvtaIDQRNH+IYHnioJNubVutLkOrVt93r/PBvgLX/KUAuFYUYIquaTQXDcjaXEbVDztDuyl1figrqpbgMlfw5to3g/V7aqN/GnyvrcNTlLWTKziFyp/3BPOr1NXsMQiaPPauCF1bXbmBrqgzi0joXS1ZZvbx+Hfr0TUNsy4w6xpmXcNi0rDU/mwx7X0s+H1Ndjm9Ew9tcj7F4aFDguXGG2/k5JNPZuLEiQ0ES1OUl5cTERHRolgBmD17NgkJCURHR3PCCSfw2GOPERvb9D6qx+PB4/GEfq6oqGj/IhQKheIQIWuC2zOmxASqly8Hw6h9wBvBh7hhgGEExYAh9zovG7Y1akOFmzwffC39BsKZQOXsXISev89Egpcrrfaz65c9tT/LkJDw9PSBGf675r+1jraigWNt3WuBIM2USLGtnITVFrx1AqtOmNR9h3rx0kDAUP9CQFWYiU14+WVjAf6AJGBIvAEDX8DA6w9+9wWat6KEWc37+ytSHAG0W7B8/PHHLF++nCVLlrTatqioiEcffZRrr722xXZTp07lrLPOIiMjg23btvG3v/2NE088kYULF6I3UYvjySef5OGHH27v1BUKheKwEHvVlYe1gvO+pDdz/GrGHcpphEgC+gJ3tdBGyjoRI0Mixus38AYM0qJVWv4/AkLKtrsr7dmzhxEjRjBjxoyQ78r48eMZMmQIL774YoO2FRUVTJo0iZiYGKZNm4bZ3HYFvH37dnr06MHPP//MhAmNw+OasrCkpaWFrDkKhUKhUCg6PxUVFURGRrbp+d2uKKFly5ZRUFDAsGHDMJlMmEwm5syZw8svv4zJZCIQCNawqKysZOrUqYSHh/PVV1+1S6wAdO/enbi4OLZu3drkeavVSkRERIMvhUKhUCgUv1/atSU0YcIE1qxZ0+DYFVdcQd++fbn77rvRdZ2KigqmTJmC1Wpl2rRp2Gy2dk8qKyuL4uJikpOT291XoVAoFArF7492WVjCw8MZMGBAgy+n00lsbCwDBgygoqKCyZMn43K5eOONN6ioqCAvL4+8vLyQ9QWgb9++fPXVV0Aw4ujOO+/kt99+Y+fOnfzyyy+cfvrp9OzZkylTphzY1SoUCoVCoTgiOaCZbpcvX86iRYsA6NmzZ4NzO3bsID09HYBNmzaFksnpus7q1at55513KCsrIyUlhcmTJ/Poo4+qXCwKhUKhUCiAdjrddlba47SjUCgUCoWic3DQnG4VCoVCoVAoDgdKsCgUCoVCoej0KMGiUCgUCoWi06MEi0KhUCgUik6PEiwKhUKhUCg6PUqwKBQKhUKh6PQowaJQKBQKhaLTowSLQqFQKBSKTs8BzXR7uKjLfVdRUXGYZ6JQKBQKhaKt1D2325LD9nchWCorKwFIS0s7zDNRKBQKhULRXiorK4mMjGyxze8iNb9hGOTk5BAeHo4Q4nBP55BRUVFBWloae/bs+cOVJFBr/2OuHf7Y61dr/2OuHX6/65dSUllZSUpKCprWspfK78LComkaqamph3sah42IiIjf1X/g9qDW/sdcO/yx16/W/sdcO/w+19+aZaUO5XSrUCgUCoWi06MEi0KhUCgUik6PEixHMFarlQcffBCr1Xq4p3LIUWv/Y64d/tjrV2v/Y64d1Prhd+J0q1AoFAqF4veNsrAoFAqFQqHo9CjBolAoFAqFotOjBItCoVAoFIpOjxIsCoVCoVAoOj1KsHRili9fzqRJk4iKiiI2NpZrr72Wqqqq0PlVq1Zx4YUXkpaWht1up1+/frz00kutjpueno4QosHXU089dTCX0m4O1tpLSkq46KKLiIiIICoqiquuuqrBuJ2F1tYPcPPNNzN8+HCsVitDhgxp07jjx49v9Lu//vrrD8IKOs7BWrvb7ebGG28kNjaWsLAwzj77bPLz8w/CCjpOW9a+e/duTj75ZBwOBwkJCdx55534/f4Wxz0S3vNw8NZ/JLzvN2/ezOmnn05cXBwREREce+yxzJo1q0GbX375hTFjxhAeHk5SUhJ33313q2s/Et7zbUUJlk5KTk4OEydOpGfPnixatIjp06ezbt06Lr/88lCbZcuWkZCQwPvvv8+6deu47777uPfee3nllVdaHf+RRx4hNzc39HXTTTcdxNW0j4O59osuuoh169YxY8YMvv32W+bOncu11157kFfUPtqy/jquvPJKzj///HaNf8011zT43T/99NMHaOb7z8Fc+2233cb//vc/PvvsM+bMmUNOTg5nnXXWAZz9/tGWtQcCAU4++WS8Xi8LFizgnXfe4e233+aBBx5odfzO/J6Hg7v+I+F9f8opp+D3+5k5cybLli1j8ODBnHLKKeTl5QHBD2knnXQSU6dOZcWKFXzyySdMmzaNe+65p9WxO/N7vl1IRafktddekwkJCTIQCISOrV69WgJyy5Ytzfa74YYb5PHHH9/i2N26dZMvvPDCgZrqAedgrX39+vUSkEuWLAkd++GHH6QQQmZnZx+YyR8A2rv+Bx98UA4ePLhNYx933HHylltuOUAzPfAcrLWXlZVJs9ksP/vss9CxDRs2SEAuXLjwgMx9f2nL2r///nupaZrMy8sLtXn11VdlRESE9Hg8zY7d2d/zUh689R8J7/vCwkIJyLlz54aOVVRUSEDOmDFDSinlvffeK0eMGNGg37Rp06TNZpMVFRXNjt3Z3/PtQVlYOikejweLxdKgGJTdbgdg3rx5zfYrLy8nJiam1fGfeuopYmNjGTp0KM8880yrZsVDycFa+8KFC4mKimLEiBGhYxMnTkTTNBYtWnQAZn5g6Oj628oHH3xAXFwcAwYM4N5776W6unq/xzxQHKy1L1u2DJ/Px8SJE0PH+vbtS9euXVm4cGHHJ3wAacvaFy5cyMCBA0lMTAy1mTJlChUVFaxbt67F8Tvzex4O3vqPhPd9bGwsffr04d1338XlcuH3+3nttddISEhg+PDhQPD+2Gy2Bv3sdjtut5tly5a1OH5nfs+3ByVYOiknnHACeXl5PPPMM3i9XkpLS0Omv9zc3Cb7LFiwgE8++aRVU+fNN9/Mxx9/zKxZs7juuut44oknuOuuuw74GjrKwVp7Xl4eCQkJDY6ZTCZiYmJCZtfOQEfW31b+9Kc/8f777zNr1izuvfde3nvvPS6++OIDMe0DwsFae15eHhaLhaioqAbHExMTO83vvi1rz8vLa/CwBkI/t7SOzv6eh4O3/iPhfS+E4Oeff2bFihWEh4djs9l4/vnnmT59OtHR0UBQmC1YsICPPvqIQCBAdnY2jzzyCNDye6Ozv+fbgxIsh5h77rmnkQPUvl8bN26kf//+vPPOOzz33HM4HA6SkpLIyMggMTGxyRLca9eu5fTTT+fBBx9k8uTJLc7h9ttvZ/z48QwaNIjrr7+e5557jn/+8594PJ6DtWygc6z9cHKw1t8err32WqZMmcLAgQO56KKLePfdd/nqq6/Ytm3bAVpl03SGtR8uOsPaD9d7HjrH+g8XbV27lJIbb7yRhIQEfv31VxYvXswZZ5zBqaeeGhIjkydP5plnnuH666/HarXSu3dvTjrpJIAW78/hes8fDFRq/kNMYWEhxcXFLbbp3r07Fosl9HN+fj5OpxMhBBEREXz88cece+65ofPr16/n+OOP5+qrr+bxxx9v95zWrVvHgAED2LhxI3369Gl3/7ZyuNf+5ptvcscdd1BaWho65vf7sdlsfPbZZ5x55pkdXFnbOBjrB3jooYf4+uuvWblyZbvn5HK5CAsLY/r06UyZMqXd/dvK4V77zJkzmTBhAqWlpQ2sLN26dePWW2/ltttua/ea2sqBXPsDDzzAtGnTGqx3x44ddO/eneXLlzN06NA2zelQvefh8K//cL7v27r2X3/9lcmTJ1NaWkpEREToXK9evbjqqqsaONZKKcnNzSU6OpqdO3eSmZnJ4sWLOeqoo9o0p0P1nj8oHF4XGkV7eOONN6TD4ZClpaWhY2vXrpUJCQnyzjvv7PC477//vtQ0TZaUlByAWR4cDsTa65zvli5dGjr2448/dirnu+Zoav11tMfpdl/mzZsnAblq1ar9m+BB5ECsvc7p9vPPPw8d27hxY6dyum2Kfdde53San58favPaa6/JiIgI6Xa72zzukfCel/LArP9IeN9PmzZNapomKysrGxzv3bu3fPzxx5vtd//998u0tDTp9/vbfK0j4T3fHEqwdGL++c9/ymXLlslNmzbJV155RdrtdvnSSy+Fzq9Zs0bGx8fLiy++WObm5oa+CgoKQm0WLVok+/TpI7OysqSUUi5YsEC+8MILcuXKlXLbtm3y/fffl/Hx8fLSSy895OtriYOxdimlnDp1qhw6dKhctGiRnDdvnuzVq5e88MILD+na2kJr65dSyi1btsgVK1bI6667Tvbu3VuuWLFCrlixIhQtkZWVJfv06SMXLVokpZRy69at8pFHHpFLly6VO3bskN98843s3r27HDdu3CFfX0scjLVLKeX1118vu3btKmfOnCmXLl0qR48eLUePHn1I19Yara3d7/fLAQMGyMmTJ8uVK1fK6dOny/j4eHnvvfeG2hyp73kpD876pez87/vCwkIZGxsrzzrrLLly5Uq5adMm+de//lWazWa5cuXKULunn35arl69Wq5du1Y+8sgj0mw2y6+++ip0/kh9z7cVJVg6MZdccomMiYmRFotFDho0SL777rsNzj/44IMSaPTVrVu3UJtZs2ZJQO7YsUNKKeWyZcvkyJEjZWRkpLTZbLJfv37yiSeeaNens0PBwVi7lFIWFxfLCy+8UIaFhcmIiAh5xRVXNPpU0xlobf1SBsMVm7oHdevdsWOHBOSsWbOklFLu3r1bjhs3TsbExEir1Sp79uwp77zzTlleXn4IV9Y6B2PtUkpZU1Mjb7jhBhkdHS0dDoc888wzZW5u7iFaVdtoy9p37twpTzzxRGm322VcXJy84447pM/nC50/Ut/zUh6c9Ut5ZLzvlyxZIidPnixjYmJkeHi4HDVqlPz+++8btDn++ONDv8eRI0c2On+kvufbivJhUSgUCoVC0ek5Ml2vFQqFQqFQ/KFQgkWhUCgUCkWnRwkWhUKhUCgUnR4lWBQKhUKhUHR6lGBRKBQKhULR6VGCRaFQKBQKRadHCRaFQqFQKBSdHiVYFAqFQqFQdHqUYFEoFAqFQtHpUYJFoVAoFApFp0cJFoVCoVAoFJ0eJVgUCoVCoVB0ev4ft7EnCcfl9hcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[4]\n",
    "print(\"what is wrong with HD\",t,\"?\")\n",
    "CONTIGUS = getContigFromStarter(HDunitList[t][0], HDunitList[t],unitNbrs)\n",
    "for u in HDunitList[t]:\n",
    "    if u in CONTIGUS:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "    else:\n",
    "        plotPoly(unitGeom[u])\n",
    "        #plotCenter(u,unitCP[u])\n",
    "plotPoly(hdCP[t].buffer(0.5))\n",
    "print(t, HDvPop[t])\n",
    "plotPoly(convexMAP)\n",
    "plt.show()\n",
    "print(\"linking bad HD\",t,\"along SW border\")\n",
    "for u in borderSet:\n",
    "    if unitCP[u].x < -91 and unitCP[u].y < 44.6 and u not in HDunitList[t]:\n",
    "        HDunitList[t] += [u]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "print(\"fixed HD\",t,\"now has pop\",HDvPop[t])\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b5cec8cd-43bb-40d0-a0fe-956403eccd62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "add unit 2 to HD 7017\n",
      "7017 now has pop 742871.395675865 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[5]\n",
    "print(\"add unit\",2,\"to HD\",t)\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({2}))\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "103b50c0-5f46-4a0e-b368-1e3a86ea6cbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "add unit 2 to HD 7018\n",
      "7018 now has pop 745163.0582697442 let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = badDiscoList[6]\n",
    "print(\"add unit\",2,\"to HD\",t)\n",
    "HDunitList[t] = list(set(HDunitList[t]).union({2}))\n",
    "HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "print(t,\"now has pop\",HDvPop[t],\"let me show you\")\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plotPoly(convexMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "acfbe2aa-1e9b-4ca8-b5f1-a8882babd9b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check contiguity after these interventions for these 7 problematic HDs\n",
      "4702 False False unbroken,noEnclave\n",
      "1956 False False unbroken,noEnclave\n",
      "1960 False False unbroken,noEnclave\n",
      "6995 False False unbroken,noEnclave\n",
      "6999 False False unbroken,noEnclave\n",
      "7017 False False unbroken,noEnclave\n",
      "7018 False False unbroken,noEnclave\n"
     ]
    }
   ],
   "source": [
    "print(\"check contiguity after these interventions for these\",len(badDiscoList),\"problematic HDs\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    print(t,unbroken,noEnclave,\"unbroken,noEnclave\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "315dc258-a9ca-4097-8008-c2d529cf433d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4702 958 5 t,contigUs, notcontigs\n",
      "only 5 discontig units, just shed them\n",
      "HD 4702 now has pop 694036.9653457933\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1956 1162 5 t,contigUs, notcontigs\n",
      "only 5 discontig units, just shed them\n",
      "HD 1956 now has pop 745997.4729202386\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1960 1185 10 t,contigUs, notcontigs\n",
      "only 10 discontig units, just shed them\n",
      "HD 1960 now has pop 743370.1173548789\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6995 1146 3 t,contigUs, notcontigs\n",
      "only 3 discontig units, just shed them\n",
      "HD 6995 now has pop 746686.0131574427\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6999 844 6 t,contigUs, notcontigs\n",
      "only 6 discontig units, just shed them\n",
      "HD 6999 now has pop 747084.0666841008\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7017 1167 8 t,contigUs, notcontigs\n",
      "only 8 discontig units, just shed them\n",
      "HD 7017 now has pop 742719.0484652536\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7018 1197 5 t,contigUs, notcontigs\n",
      "only 5 discontig units, just shed them\n",
      "HD 7018 now has pop 744125.0824254609\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in badDiscoList:\n",
    "    plotPoly(hdCP[t].buffer(0.5))\n",
    "    CONTIGUS  = getContigFromStarter(HDunitList[t][0],HDunitList[t],unitNbrs)\n",
    "    NONCONTIGS = list(set(HDunitList[t]).difference(set(CONTIGUS)))\n",
    "    print(t,len(CONTIGUS),len(NONCONTIGS),\"t,contigUs, notcontigs\")\n",
    "    for u in HDunitList[t]:\n",
    "        if u in NONCONTIGS:\n",
    "            plotPoly(unitGeom[u])\n",
    "        else:\n",
    "            plotPoly(unitCP[u].buffer(0.01))\n",
    "    if len(NONCONTIGS) < 12:\n",
    "        print(\"only\",len(NONCONTIGS),\"discontig units, just shed them\")\n",
    "        HDunitList[t] = CONTIGUS.copy()\n",
    "        HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "        print(\"HD\",t,\"now has pop\", HDvPop[t])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4f2f9061-e977-44c1-8791-fecb7745c9dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, fill in enclaves as needed on these 7\n",
      "working on enclave-y HD 4702 . We have evaluated 0 of 0 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 6995 . We have evaluated 3 of 0 enclavy HDs.Time is now 1\n",
      "working on enclave-y HD 7018 . We have evaluated 6 of 0 enclavy HDs.Time is now 2\n"
     ]
    }
   ],
   "source": [
    "print(\"now, fill in enclaves as needed on these\",len(badDiscoList))\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(badDiscoList):  #internals + edgers):  #cantFill\n",
    "    if iii%3 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(enclaveOnly),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        #tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            print(\"we didn't need to fix HD\",t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b78199da-ac7c-4cfb-ac0b-26363a8a8c56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prev avg use and its sd are 1.01134 0.12148\n",
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01136 0.12147\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"prev avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "a2242181-3a07-40b7-ae56-bbe47bd2dc79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 2 time is now 0 sec\n",
      "working on HD 534 time is now 9 sec\n",
      "working on HD 1127 time is now 18 sec\n",
      "working on HD 1645 time is now 30 sec\n",
      "working on HD 2164 time is now 38 sec\n",
      "working on HD 2676 time is now 48 sec\n",
      "working on HD 3210 time is now 58 sec\n",
      "working on HD 3746 time is now 66 sec\n",
      "working on HD 4276 time is now 75 sec\n",
      "working on HD 4786 time is now 83 sec\n",
      "working on HD 5302 time is now 95 sec\n",
      "working on HD 5814 time is now 103 sec\n",
      "working on HD 6338 time is now 112 sec\n",
      "working on HD 6879 time is now 122 sec\n",
      "out of 6678 total HDs, there were 6678 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 125 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "de4d8af8-cc64-4215-9b95-f4c6a2bd03af",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedAgainUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "f4bb76c7-0ae0-40cb-9c6a-ee436dfc30c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDunitList = [savedAgainUnitList[t].copy() for t in range(nHDs)]  #restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "f3bcd6a8-40b6-4764-a0d1-6814e3286cb8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking on our corner clusters and unit county usage\n",
      "usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\n",
      "0.90069     0     13317 0.5\n",
      "1.19236     1     4255 0.5\n",
      "0.83031     2     7318 0.5\n",
      "1.13144     3     14188 0.5\n",
      "0.99792     6836     13737 0.25\n",
      "1.00757     6837     169151 0.25\n",
      "1.0033     6838     171003 0.25\n",
      "1.02415     6839     92501 0.25\n",
      "1.02508     6840     51938 0.25\n"
     ]
    }
   ],
   "source": [
    "print(\"checking on our corner clusters and unit county usage\")\n",
    "print(\"usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\")\n",
    "for u in range(nUnits):\n",
    "    if int(allUnits[u]) != allUnits[u] :\n",
    "        print(r5(unitUse[u]),\"   \",u,\"   \",int(unitPop[u]), allUnits[u]%1 )\n",
    "# note for MN, option 3 here led to tight CCB unit usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1e983c03-777a-4e81-bed0-34a620175f83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9bc31b5a-992d-4a38-b9fe-3470b55e1e2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6150cac-2249-415b-a364-edf55dc441ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "114705bb-9640-45f1-9f25-030030efaa63",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below here -- working on tightening use distro while squaring up pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5d7d8519-eb3d-4345-9ac6-ab888e61c348",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.01133 0.12145\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "b1971853-bda7-49a4-9f25-1bdfd5e75aa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 2\n",
      "working on avg unit-to-HDcp dist for HD 909\n",
      "working on avg unit-to-HDcp dist for HD 1751\n",
      "working on avg unit-to-HDcp dist for HD 2573\n",
      "working on avg unit-to-HDcp dist for HD 3418\n",
      "working on avg unit-to-HDcp dist for HD 4276\n",
      "working on avg unit-to-HDcp dist for HD 5092\n",
      "working on avg unit-to-HDcp dist for HD 5923\n",
      "working on avg unit-to-HDcp dist for HD 6762\n"
     ]
    }
   ],
   "source": [
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f5b99900-614a-47df-b7de-5d59fffd6d3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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bG6udO3d6VCMAAOhfePcTAAAwAqEGAAAYgVADAACMQKgBAABGINQAAAAjEGoAAIARCDUAAMAIhBoAAGAEQg0AADACoQYAABiBUAMAAIxAqAEAAEYg1AAAACMQagAAgBEINQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABgBEINAAAwAqEGAAAYgVADAACMQKgBAABGINQAAAAjEGoAAIARCDUAAMAIhBoAAGAEQg0AADACoQYAABiBUAMAAIxAqAEAAEYg1AAAACMQagAAgBG6FGrWrl2ruLg4BQYGKjk5WXv27Dlv388++0wZGRmKi4uTn5+fCgsLuzTmd999p4ULFyo8PFyDBw9WRkaGamtru1I+AAAwkMehpqSkRHa7XXl5eaqsrFR8fLzS09NVV1fXaf/Tp09r1KhRWrFihWw2W5fHXLx4sX73u99p06ZN2rlzp44ePaq7777b0/IBAIChPA41BQUFmj9/vrKzszV+/HgVFRVp0KBBWr9+faf9p06dqpUrV2rWrFkKCAjo0pgNDQ1at26dCgoKdOuttyoxMVEbNmzQrl279PHHH3u6CwAAwEAehZrW1lZVVFQoLS3txwEsFqWlpam8vLxLBVzMmBUVFWpra3PrM27cOF1++eXn3W5LS4saGxvdFgAAYC6PQs2JEyfU3t6uqKgot/aoqCg5HI4uFXAxYzocDlmtVoWFhV30dvPz8xUaGupaYmNju1QfAADoG4y9+yk3N1cNDQ2u5auvvurpkgAAgA8N8KRzRESE/P39z7nrqLa29ryTgL0xps1mU2trq+rr693O1lxouwEBAeedwwMAAMzj0Zkaq9WqxMRElZWVudo6OjpUVlamlJSULhVwMWMmJiZq4MCBbn0OHTqk6urqLm8XAACYxaMzNZJkt9uVlZWlKVOmKCkpSYWFhWpublZ2drYkae7cuYqJiVF+fr6k7ycCHzhwwPV3TU2NqqqqNHjwYI0ZM+aixgwNDdW8efNkt9s1bNgwhYSE6NFHH1VKSoquu+46rxwIAADQt3kcajIzM3X8+HEtXbpUDodDCQkJKi0tdU30ra6ulsXy4wmgo0ePavLkya7Pq1at0qpVq5SamqodO3Zc1JiS9NJLL8lisSgjI0MtLS1KT0/Xa6+91tX9BgAAhvFzOp3Oni6iOzQ2Nio0NFQNDQ0KCQnp6XKAXmt/TYN+/upHevfRGzUhJrSny7kofbFmABfHk99vY+9+AgAA/QuhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABgBEINAAAwgsevSQDgmZr6MzrZ3OqTsYcGWxUTFuSTsQGgryHUAD5UU39Gaat36kxbu0/GDxror+1PpBJsAECEGsCnTja36kxbuwozEzQmcrBXxz5c16RFJVU62dxKqAEAEWqAbjEmcjAvWgQAHyPUAH3c4bqmXj0eAHQXQg3QRw0NtipooL8WlVR5feyggf4aGmz1+rgA4EuEGqCPigkL0vYnUn1yZxV3VQHoiwg1QB8WExZE+ACA/4eH7wEAACMQagAAgBEINQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABgBEINAAAwAqEGAAAYgVADAACMQKgBAABGINQAAAAjEGoAAIARCDUAAMAIhBoAAGCELoWatWvXKi4uToGBgUpOTtaePXsu2H/Tpk0aN26cAgMDNXHiRG3dutXtez8/v06XlStXuvrExcWd8/2KFSu6Uj4AADCQx6GmpKREdrtdeXl5qqysVHx8vNLT01VXV9dp/127dmn27NmaN2+e9u3bp5kzZ2rmzJnav3+/q8+xY8fclvXr18vPz08ZGRluYz3//PNu/R599FFPywcAAIbyONQUFBRo/vz5ys7O1vjx41VUVKRBgwZp/fr1nfZ/+eWXNX36dD355JO6+uqr9cILL+jaa6/VmjVrXH1sNpvb8tvf/la33HKLRo0a5TbWkCFD3PoFBwd7Wj4AADCUR6GmtbVVFRUVSktL+3EAi0VpaWkqLy/vdJ3y8nK3/pKUnp5+3v61tbV67733NG/evHO+W7FihcLDwzV58mStXLlSZ8+e9aR8AABgsAGedD5x4oTa29sVFRXl1h4VFaWDBw92uo7D4ei0v8Ph6LT/r371Kw0ZMkR33323W/tjjz2ma6+9VsOGDdOuXbuUm5urY8eOqaCgoNNxWlpa1NLS4vrc2Nj4k/sHAAD6Lo9CTXdYv3695syZo8DAQLd2u93u+nvSpEmyWq165JFHlJ+fr4CAgHPGyc/P1/Lly31eLwAA6B08uvwUEREhf39/1dbWurXX1tbKZrN1uo7NZrvo/h9++KEOHTqkhx566CdrSU5O1tmzZ/WXv/yl0+9zc3PV0NDgWr766qufHBMAAPRdHoUaq9WqxMRElZWVudo6OjpUVlamlJSUTtdJSUlx6y9J27Zt67T/unXrlJiYqPj4+J+spaqqShaLRZGRkZ1+HxAQoJCQELcFAACYy+PLT3a7XVlZWZoyZYqSkpJUWFio5uZmZWdnS5Lmzp2rmJgY5efnS5Ief/xxpaamavXq1ZoxY4Y2btyovXv36o033nAbt7GxUZs2bdLq1avP2WZ5ebl2796tW265RUOGDFF5ebkWL16s+++/X0OHDu3KfgMAAMN4HGoyMzN1/PhxLV26VA6HQwkJCSotLXVNBq6urpbF8uMJoOuvv17FxcVasmSJnn32WY0dO1ZbtmzRhAkT3MbduHGjnE6nZs+efc42AwICtHHjRi1btkwtLS0aOXKkFi9e7DbPBgAA9G9+TqfT2dNFdIfGxkaFhoaqoaGBS1HoNvtrGvTzVz/Su4/eqAkxoT1djrE4zoC5PPn95t1PAADACIQaAABgBEINAAAwAqEGAAAYodc9URjoCTX1Z3SyudXr4x6ua/L6mACAzhFq0O/V1J9R2uqdOtPW7pPxgwb6a2iw1SdjAwB+RKhBv3eyuVVn2tpVmJmgMZGDvT7+0GCrYsKCvD4uAMAdoQb4f8ZEDuYZJwDQhxFqABjDV3OYONsG9A2EGgB93tBgq4IG+mtRSZVPxg8a6K/tT6QSbIBejlADoM+LCQvS9idSfXYH26KSKp1sbiXUAL0coQaAEWLCgggdQD/Hw/cAAIARCDUAAMAIhBoAAGAEQg0AADACoQYAABiBUAMAAIxAqAEAAEYg1AAAACMQagAAgBEINQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABgBEINAAAwAqEGAAAYYUBPFwAA8L6a+jM62dzq9XGHBlsVExbk9XEBbyDUAIBhaurPKG31Tp1pa/f62EED/bX9iVSCDXolQg0AGOZkc6vOtLWrMDNBYyIHe23cw3VNWlRSpZPNrYQa9EqEGgAw1JjIwZoQE9rTZQDdhonCAADACF0KNWvXrlVcXJwCAwOVnJysPXv2XLD/pk2bNG7cOAUGBmrixInaunWr2/cPPPCA/Pz83Jbp06e79fn22281Z84chYSEKCwsTPPmzVNTU1NXygcAjx2ua9L+mgavLjX1Z3p6twCjeHz5qaSkRHa7XUVFRUpOTlZhYaHS09N16NAhRUZGntN/165dmj17tvLz8/Xzn/9cxcXFmjlzpiorKzVhwgRXv+nTp2vDhg2uzwEBAW7jzJkzR8eOHdO2bdvU1tam7OxsPfzwwyouLvZ0FwDgog0NtipooL8WlVR5fWwm3QLe5XGoKSgo0Pz585WdnS1JKioq0nvvvaf169frmWeeOaf/yy+/rOnTp+vJJ5+UJL3wwgvatm2b1qxZo6KiIle/gIAA2Wy2Trf5+eefq7S0VJ988ommTJkiSXr11Vd1xx13aNWqVYqOjvZ0NwDgosSEBWn7E6levz2aSbeA93kUalpbW1VRUaHc3FxXm8ViUVpamsrLyztdp7y8XHa73a0tPT1dW7ZscWvbsWOHIiMjNXToUN1666365S9/qfDwcNcYYWFhrkAjSWlpabJYLNq9e7fuuuuuc7bb0tKilpYW1+fGxkZPdhUAXGLCgggeQB/g0ZyaEydOqL29XVFRUW7tUVFRcjgcna7jcDh+sv/06dP161//WmVlZfqP//gP7dy5U7fffrva29tdY/z9pa0BAwZo2LBh591ufn6+QkNDXUtsbKwnuwoAAPqYXnFL96xZs1x/T5w4UZMmTdLo0aO1Y8cOTZs2rUtj5ubmup0hamxsJNgYwBdPST1cx4RzADCBR6EmIiJC/v7+qq2tdWuvra0973wYm83mUX9JGjVqlCIiInT48GFNmzZNNptNdXV1bn3Onj2rb7/99rzjBAQEnDPZGH2br5+SOjTY6vVxAQDdx6NQY7ValZiYqLKyMs2cOVOS1NHRobKyMuXk5HS6TkpKisrKyrRo0SJX27Zt25SSknLe7Xz99df65ptvNGLECNcY9fX1qqioUGJioiTp/fffV0dHh5KTkz3ZBfRhvnpKqsT7bADABB5ffrLb7crKytKUKVOUlJSkwsJCNTc3u+6Gmjt3rmJiYpSfny9Jevzxx5WamqrVq1drxowZ2rhxo/bu3as33nhDktTU1KTly5crIyNDNptNR44c0VNPPaUxY8YoPT1dknT11Vdr+vTpmj9/voqKitTW1qacnBzNmjWLO5/6IZ6SCgDojMehJjMzU8ePH9fSpUvlcDiUkJCg0tJS12Tg6upqWSw/zj++/vrrVVxcrCVLlujZZ5/V2LFjtWXLFtczavz9/fXpp5/qV7/6lerr6xUdHa3bbrtNL7zwgtvlo7feeks5OTmaNm2aLBaLMjIy9Morr1zq/gMAAEN0aaJwTk7OeS837dix45y2e+65R/fcc0+n/YOCgvT73//+J7c5bNgwHrQHwDi+mKjO5Hf0V73i7icA6G98+aRiicnv6J8INQDQA3z1pOIfMPkd/RGhBgB6CE8qBryrS2/pBgAA6G0INQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABgBEINAAAwAqEGAAAYgVADAACMQKgBAABGGNDTBQAA+pbDdU0+GXdosFUxYUE+GRv9A6EGAHBRhgZbFTTQX4tKqnwyftBAf21/IpVggy4j1AAALkpMWJC2P5Gqk82tXh/7cF2TFpVU6WRzK6EGXUaoAQBctJiwIEIHei0mCgMAACMQagAAgBEINQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARuDhe/C6mvozPnviKAAA50OogVfV1J9R2uqdOtPW7pPxgwb6a2iw1SdjAwD6NkINvOpkc6vOtLWrMDNBYyIHe3183uILADgfQg18YkzkYE2ICe3pMgAA/QgThQEAgBEINQAAwAiEGgAAYARCDQAAMEKXQs3atWsVFxenwMBAJScna8+ePRfsv2nTJo0bN06BgYGaOHGitm7d6vqura1NTz/9tCZOnKjg4GBFR0dr7ty5Onr0qNsYcXFx8vPzc1tWrFjRlfIBAICBPA41JSUlstvtysvLU2VlpeLj45Wenq66urpO++/atUuzZ8/WvHnztG/fPs2cOVMzZ87U/v37JUmnT59WZWWlnnvuOVVWVmrz5s06dOiQ/vEf//GcsZ5//nkdO3bMtTz66KOelg8AAAzlcagpKCjQ/PnzlZ2drfHjx6uoqEiDBg3S+vXrO+3/8ssva/r06XryySd19dVX64UXXtC1116rNWvWSJJCQ0O1bds23Xvvvbrqqqt03XXXac2aNaqoqFB1dbXbWEOGDJHNZnMtwcHBXdhlAABgIo9CTWtrqyoqKpSWlvbjABaL0tLSVF5e3uk65eXlbv0lKT09/bz9JamhoUF+fn4KCwtza1+xYoXCw8M1efJkrVy5UmfPnj3vGC0tLWpsbHRbAACAuTx6+N6JEyfU3t6uqKgot/aoqCgdPHiw03UcDken/R0OR6f9v/vuOz399NOaPXu2QkJCXO2PPfaYrr32Wg0bNky7du1Sbm6ujh07poKCgk7Hyc/P1/Llyz3ZPQAA0If1qicKt7W16d5775XT6dTrr7/u9p3dbnf9PWnSJFmtVj3yyCPKz89XQEDAOWPl5ua6rdPY2KjY2FjfFQ8AAHqUR6EmIiJC/v7+qq2tdWuvra2VzWbrdB2bzXZR/X8INH/961/1/vvvu52l6UxycrLOnj2rv/zlL7rqqqvO+T4gIKDTsAMAAMzk0Zwaq9WqxMRElZWVudo6OjpUVlamlJSUTtdJSUlx6y9J27Ztc+v/Q6D54osvtH37doWHh/9kLVVVVbJYLIqMjPRkFwAAgKE8vvxkt9uVlZWlKVOmKCkpSYWFhWpublZ2drYkae7cuYqJiVF+fr4k6fHHH1dqaqpWr16tGTNmaOPGjdq7d6/eeOMNSd8Hmn/+539WZWWl3n33XbW3t7vm2wwbNkxWq1Xl5eXavXu3brnlFg0ZMkTl5eVavHix7r//fg0dOtRbxwIAAPRhHoeazMxMHT9+XEuXLpXD4VBCQoJKS0tdk4Grq6tlsfx4Auj6669XcXGxlixZomeffVZjx47Vli1bNGHCBElSTU2N/ud//keSlJCQ4LatP/7xj7r55psVEBCgjRs3atmyZWppadHIkSO1ePFitzkzAIC+73Bdk9fHHBpsVUxYkNfHRe/j53Q6nT1dRHdobGxUaGioGhoafnK+Drpuf02Dfv7qR3r30Rs1ISa0p8sB0EfU1J9R2uqdOtPW7vWxgwb6a/sTqQSbPsqT3+9edfcTAKB/igkL0vYnUnWyudWr4x6ua9KikiqdbG4l1PQDhBoAQK8QExZE8MAl4S3dAADACIQaAABgBEINAAAwAqEGAAAYgVADAACMQKgBAABGINQAAAAjEGoAAIARCDUAAMAIhBoAAGAEQg0AADACoQYAABiBF1oCAIx3uK7JJ+MODbbyEs5ehFADADDW0GCrggb6a1FJlU/GDxror+1PpBJseglCDQDAWDFhQdr+RKpONrd6fezDdU1aVFKlk82thJpeglDTj9XUn/H6P+i+OsULAF0VExZE6OgnCDX9VE39GaWt3qkzbe1eHztooL+GBlu9Pi4AABdCqOmnTja36kxbuwozEzQmcrBXx2biHACgJxBq+rkxkYM1ISa0p8sAAOCS8ZwaAABgBM7U9HK+mMwrMaEXALyFZ+D0HoQaL/FF+PimuVUL/r8Kn0zmlZjQCwCXgmfg9D6EGi/w9Z1Ev3owSeE+CB/8VwAAdB3PwOl9CDVewJ1EANA/+foZOL64tGXy7wqhxou4kwgA4A2+vLRl8mUtQg0AAL2Mry5tmX5Zi1ADAEAvxOsdPMdzagAAgBEINQAAwAiEGgAAYARCDQAAMAIThQEA6GdMfbUDoQYAgH7C9Fc7EGoAAOgnTH+1A6EGAIB+xOTn3zBRGAAAGKFLoWbt2rWKi4tTYGCgkpOTtWfPngv237Rpk8aNG6fAwEBNnDhRW7dudfve6XRq6dKlGjFihIKCgpSWlqYvvvjCrc+3336rOXPmKCQkRGFhYZo3b56amnwz0QkAAPQ9HoeakpIS2e125eXlqbKyUvHx8UpPT1ddXV2n/Xft2qXZs2dr3rx52rdvn2bOnKmZM2dq//79rj4vvviiXnnlFRUVFWn37t0KDg5Wenq6vvvuO1efOXPm6LPPPtO2bdv07rvv6oMPPtDDDz/chV0GAABGcnooKSnJuXDhQtfn9vZ2Z3R0tDM/P7/T/vfee69zxowZbm3JycnORx55xOl0Op0dHR1Om83mXLlypev7+vp6Z0BAgPPtt992Op1O54EDB5ySnJ988omrz//+7/86/fz8nDU1NRdVd0NDg1OSs6Gh4eJ21AN/+rreecXT7zr/9HW918cGAKAv8NVvoSe/3x5NFG5tbVVFRYVyc3NdbRaLRWlpaSovL+90nfLyctntdre29PR0bdmyRZL05ZdfyuFwKC0tzfV9aGiokpOTVV5erlmzZqm8vFxhYWGaMmWKq09aWposFot2796tu+6665zttrS0qKWlxfW5oaFBktTY2OjJLl+UplON6mg5raZTjWps9PP6+AAA9Ha++i384Xfb6XT+ZF+PQs2JEyfU3t6uqKgot/aoqCgdPHiw03UcDken/R0Oh+v7H9ou1CcyMtK98AEDNGzYMFefv5efn6/ly5ef0x4bG3u+3btkKYU+GxoAgD7BV7+Fp06dUmho6AX7GHtLd25urtsZoo6ODn377bcKDw+Xn5/vzqY0NjYqNjZWX331lUJCQny2nd6qv++/xDGQOAYSx0DiGPT3/Ze8cwycTqdOnTql6Ojon+zrUaiJiIiQv7+/amtr3dpra2tls9k6Xcdms12w/w//W1tbqxEjRrj1SUhIcPX5+4nIZ8+e1bfffnve7QYEBCggIMCtLSws7MI76EUhISH99v/EEvsvcQwkjoHEMZA4Bv19/6VLPwY/dYbmBx7d/WS1WpWYmKiysjJXW0dHh8rKypSSktLpOikpKW79JWnbtm2u/iNHjpTNZnPr09jYqN27d7v6pKSkqL6+XhUVFa4+77//vjo6OpScnOzJLgAAAEN5fPnJbrcrKytLU6ZMUVJSkgoLC9Xc3Kzs7GxJ0ty5cxUTE6P8/HxJ0uOPP67U1FStXr1aM2bM0MaNG7V371698cYbkiQ/Pz8tWrRIv/zlLzV27FiNHDlSzz33nKKjozVz5kxJ0tVXX63p06dr/vz5KioqUltbm3JycjRr1qyLOh0FAADM53GoyczM1PHjx7V06VI5HA4lJCSotLTUNdG3urpaFsuPJ4Cuv/56FRcXa8mSJXr22Wc1duxYbdmyRRMmTHD1eeqpp9Tc3KyHH35Y9fX1uvHGG1VaWqrAwEBXn7feeks5OTmaNm2aLBaLMjIy9Morr1zKvvtEQECA8vLyzrn01V/09/2XOAYSx0DiGEgcg/6+/1L3HwM/58XcIwUAANDL8e4nAABgBEINAAAwAqEGAAAYgVADAACMQKjpgrVr1youLk6BgYFKTk7Wnj17ztv35ptvlp+f3znLjBkzurFi7/Jk/yWpsLBQV111lYKCghQbG6vFixe7vYG9L/LkGLS1ten555/X6NGjFRgYqPj4eJWWlnZjtd73wQcf6M4771R0dLT8/Pxc73K7kB07dujaa69VQECAxowZozfffNPndfqKp/t/7Ngx3XfffbryyitlsVi0aNGibqnTlzw9Bps3b9bPfvYzDR8+XCEhIUpJSdHvf//77inWRzw9Bh999JFuuOEGhYeHKygoSOPGjdNLL73UPcX6SFf+XfCD//u//9OAAQNcD9r1BkKNh0pKSmS325WXl6fKykrFx8crPT39nCce/2Dz5s06duyYa9m/f7/8/f11zz33dHPl3uHp/hcXF+uZZ55RXl6ePv/8c61bt04lJSV69tlnu7ly7/H0GCxZskT/+Z//qVdffVUHDhzQggULdNddd2nfvn3dXLn3NDc3Kz4+XmvXrr2o/l9++aVmzJihW265RVVVVVq0aJEeeuihPvuj5un+t7S0aPjw4VqyZIni4+N9XF338PQYfPDBB/rZz36mrVu3qqKiQrfccovuvPPOfvXPQXBwsHJycvTBBx/o888/15IlS7RkyRLXc9v6Ik+PwQ/q6+s1d+5cTZs2zbsFefX94P1AUlKSc+HCha7P7e3tzujoaGd+fv5Frf/SSy85hwwZ4mxqavJViT7l6f4vXLjQeeutt7q12e125w033ODTOn3J02MwYsQI55o1a9za7r77buecOXN8Wmd3keT8zW9+c8E+Tz31lPOaa65xa8vMzHSmp6f7sLLucTH7/7dSU1Odjz/+uM/q6QmeHoMfjB8/3rl8+XLvF9QDunoM7rrrLuf999/v/YJ6gCfHIDMz07lkyRJnXl6eMz4+3ms1cKbGA62traqoqFBaWpqrzWKxKC0tTeXl5Rc1xrp16zRr1iwFBwf7qkyf6cr+X3/99aqoqHBdnvnzn/+srVu36o477uiWmr2tK8egpaXF7UGSkhQUFKSPPvrIp7X2JuXl5W7HTJLS09Mv+p8bmKejo0OnTp3SsGHDerqUHrNv3z7t2rVLqampPV1Kt9qwYYP+/Oc/Ky8vz+tjG/uWbl84ceKE2tvbXU9P/kFUVJQOHjz4k+vv2bNH+/fv17p163xVok91Zf/vu+8+nThxQjfeeKOcTqfOnj2rBQsW9NnLT105Bunp6SooKNBNN92k0aNHq6ysTJs3b1Z7e3t3lNwrOByOTo9ZY2Ojzpw5o6CgoB6qDD1l1apVampq0r333tvTpXS7yy67TMePH9fZs2e1bNkyPfTQQz1dUrf54osv9Mwzz+jDDz/UgAHejyCcqelG69at08SJE5WUlNTTpXSbHTt26N///d/12muvqbKyUps3b9Z7772nF154oadL6zYvv/yyxo4dq3HjxslqtSonJ0fZ2dlurxMB+pPi4mItX75c77zzjiIjI3u6nG734Ycfau/evSoqKlJhYaHefvvtni6pW7S3t+u+++7T8uXLdeWVV/pkG5yp8UBERIT8/f1VW1vr1l5bWyubzXbBdZubm7Vx40Y9//zzvizRp7qy/88995x+8YtfuP5LZOLEia73fP3bv/1bn/th78oxGD58uLZs2aLvvvtO33zzjaKjo/XMM89o1KhR3VFyr2Cz2To9ZiEhIZyl6Wc2btyohx56SJs2bTrnkmR/MXLkSEnf//uwtrZWy5Yt0+zZs3u4Kt87deqU9u7dq3379iknJ0fS95chnU6nBgwYoD/84Q+69dZbL2kbfesXpYdZrVYlJiaqrKzM1dbR0aGysjKlpKRccN1NmzappaVF999/v6/L9Jmu7P/p06fPCS7+/v6SJGcffO3Ypfx/IDAwUDExMTp79qz++7//W//0T//k63J7jZSUFLdjJknbtm37yWMGs7z99tvKzs7W22+/3acfa+FNHR0damlp6ekyukVISIj+9Kc/qaqqyrUsWLBAV111laqqqpScnHzJ2+BMjYfsdruysrI0ZcoUJSUlqbCwUM3NzcrOzpYkzZ07VzExMcrPz3dbb926dZo5c6bCw8N7omyv8XT/77zzThUUFGjy5MlKTk7W4cOH9dxzz+nOO+90hZu+xtNjsHv3btXU1CghIUE1NTVatmyZOjo69NRTT/XkblySpqYmHT582PX5yy+/VFVVlYYNG6bLL79cubm5qqmp0a9//WtJ0oIFC7RmzRo99dRTevDBB/X+++/rnXfe0XvvvddTu3BJPN1/SaqqqnKte/z4cVVVVclqtWr8+PHdXb5XeHoMiouLlZWVpZdfflnJyclyOBySvp80Hxoa2iP7cKk8PQZr167V5ZdfrnHjxkn6/jb3VatW6bHHHuuR+r3Bk2NgsVg0YcIEt/UjIyMVGBh4TnuXee0+qn7k1VdfdV5++eVOq9XqTEpKcn788ceu71JTU51ZWVlu/Q8ePOiU5PzDH/7QzZX6hif739bW5ly2bJlz9OjRzsDAQGdsbKzzX/7lX5wnT57s/sK9yJNjsGPHDufVV1/tDAgIcIaHhzt/8YtfOGtqanqgau/54x//6JR0zvLDfmdlZTlTU1PPWSchIcFptVqdo0aNcm7YsKHb6/aWrux/Z/2vuOKKbq/dWzw9BqmpqRfs3xd5egxeeeUV5zXXXOMcNGiQMyQkxDl58mTna6+95mxvb++ZHfCCrvyz8Le8fUu3n9PZB68BAAAA/B3m1AAAACMQagAAgBEINQAAwAiEGgAAYARCDQAAMAKhBgAAGIFQAwAAjECoAQAARiDUAAAAIxBqAACAEQg1AADACIQaAABghP8fIghixQe7n88AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.01133 0.12145\n"
     ]
    }
   ],
   "source": [
    "#Restart - may want to comment out first line\n",
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, weights = unitPop,bins = 50)\n",
    "plt.show()\n",
    "plt.hist([HDvPop[t] for t in popHDlist], bins=50)\n",
    "plt.show()\n",
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cea58fc2-c389-474a-9800-0f4906640a27",
   "metadata": {},
   "outputs": [],
   "source": [
    "#WA - OPTIONAL restart here, pull in file*********************\n",
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for squaring up\") \n",
    "print(\"Must have already established unitGeoms, pops, topology in above blocks\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigButOffPopUnit.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse,weights = unitPop)\n",
    "print(\"weighted unit use histogram\")\n",
    "plt.show()\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "df4138f4-7e93-464a-b926-9291b5f68a04",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 1\n",
      "working on avg unit-to-HDcp dist for HD 821\n",
      "working on avg unit-to-HDcp dist for HD 1627\n",
      "working on avg unit-to-HDcp dist for HD 2450\n",
      "working on avg unit-to-HDcp dist for HD 3253\n",
      "working on avg unit-to-HDcp dist for HD 4067\n",
      "working on avg unit-to-HDcp dist for HD 4882\n",
      "working on avg unit-to-HDcp dist for HD 5689\n",
      "working on avg unit-to-HDcp dist for HD 6496\n",
      "working on avg unit-to-HDcp dist for HD 7315\n"
     ]
    }
   ],
   "source": [
    "#  *****NOTE FOR WI -- VERY SLOW POP-SQUARING -- RAN OVER MULTIPLE DAYS WITH PAUSES -- NOT A TYPICAL STATE *****"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 898 HDs with pop < 729347 to within 599\n",
      "working on squaring up HD 12 time is now 0\n",
      "working on squaring up HD 802 time is now 5248\n",
      "working on squaring up HD 1638 time is now 10567\n",
      "working on squaring up HD 2107 time is now 15156\n",
      "working on squaring up HD 2842 time is now 29141\n",
      "working on squaring up HD 3710 time is now 30828\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[64], line 30\u001b[0m\n\u001b[0;32m     28\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[i]   \u001b[38;5;66;03m#nearHDscore.index(np.min(nearHDscore))\u001b[39;00m\n\u001b[0;32m     29\u001b[0m unitNoToAdd \u001b[38;5;241m=\u001b[39m nearHDlist[listNo]  \u001b[38;5;66;03m#add this unit ...\u001b[39;00m\n\u001b[1;32m---> 30\u001b[0m canAdd  \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43munitNoToAdd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcurrList\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     31\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m canAdd: \n\u001b[0;32m     32\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 809\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    807\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    808\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 809\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    811\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.99 * aDP, 1.01 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop)\n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) ) \n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "b09a3f43-8d69-4430-8811-e3cfacf2c0e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "512\n",
      "continuing square-up after pause above\n",
      "continuing to square up the 898 HDs with pop < 729347 to within 599\n",
      "working on squaring up HD 3783 time is now 69883\n",
      "working on squaring up HD 3887 time is now 70572\n",
      "working on squaring up HD 4223 time is now 70592\n",
      "working on squaring up HD 4406 time is now 72333\n",
      "working on squaring up HD 4583 time is now 75033\n",
      "working on squaring up HD 4785 time is now 75774\n",
      "working on squaring up HD 4889 time is now 75830\n",
      "working on squaring up HD 4980 time is now 75980\n",
      "working on squaring up HD 5187 time is now 76244\n",
      "working on squaring up HD 5502 time is now 76270\n",
      "working on squaring up HD 5745 time is now 76432\n",
      "working on squaring up HD 5846 time is now 77206\n",
      "working on squaring up HD 5972 time is now 77546\n",
      "working on squaring up HD 6123 time is now 79859\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[67], line 23\u001b[0m\n\u001b[0;32m     21\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[i]   \u001b[38;5;66;03m#nearHDscore.index(np.min(nearHDscore))\u001b[39;00m\n\u001b[0;32m     22\u001b[0m unitNoToAdd \u001b[38;5;241m=\u001b[39m nearHDlist[listNo]  \u001b[38;5;66;03m#add this unit ...\u001b[39;00m\n\u001b[1;32m---> 23\u001b[0m canAdd  \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43munitNoToAdd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcurrList\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     24\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m canAdd: \n\u001b[0;32m     25\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 809\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    807\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    808\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 809\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    811\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "print(ii)\n",
    "print(\"continuing square-up after pause above\")\n",
    "print(\"continuing to square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) ) \n",
    "for ii,t in enumerate(underPoppedList[512: ] ): #underpoppedList\n",
    "    if ii%20 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "9245784c-a444-4062-bcb2-40cac544277b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "273 7058\n",
      "7057 898\n"
     ]
    }
   ],
   "source": [
    "print(ii,t)\n",
    "print(underPoppedList[897], len(underPoppedList))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "219aa49b-8618-4150-85ec-108762374258",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "intermediate save on slow state\n"
     ]
    }
   ],
   "source": [
    "print(\"intermediate save on slow state\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigMostUnderPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "amped unit avg and sd usage are 1.01583 0.11941\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#prevUnitUse = [0.]*nUnits\n",
    "#for t in popHDlist:\n",
    "#    for u in latestHDlist[t]:\n",
    "#        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "#print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "44eb5aaf-4293-4fe1-9d32-6a98d5e74973",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n"
     ]
    }
   ],
   "source": [
    "remainingUnderPoppedList = list()\n",
    "for t in range(nHDs):\n",
    "    if HDvPop[t] > 0.8 * aDP and HDvPop[t] < 0.98 * aDP:\n",
    "        remainingUnderPoppedList.append(t)\n",
    "print(len(remainingUnderPoppedList))\n",
    "ender = remainingUnderPoppedList[0]\n",
    "remainingUnderPoppedList.remove(ender)\n",
    "remainingUnderPoppedList += [ender]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "536dcab8-5032-4f79-a91c-7bedb76286a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing square-up after pause above\n",
      "continuing to square up the 898 HDs with pop < 729347 to within 599\n",
      "working on squaring up HD 6821 time is now 0\n",
      "working on squaring up HD 6827 time is now 10\n",
      "working on squaring up HD 6834 time is now 551\n",
      "working on squaring up HD 7008 time is now 1616\n",
      "working on squaring up HD 7049 time is now 1787\n",
      "We have addressed underpop in a total of 898 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"continuing square-up after pause above\")  #SHOULD BE FINAL UNDERPOP BLOCK\n",
    "print(\"continuing to square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "for ii,t in enumerate(remainingUnderPoppedList): #underpoppedList\n",
    "    if ii%3 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "1112d1a4-469d-4a7b-a0c2-ff736de82845",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "intermediate save on slow state\n"
     ]
    }
   ],
   "source": [
    "print(\"intermediate save on slow state\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigAllUnderPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "bb0be525-b8f4-4763-94e6-09fc491b833c",
   "metadata": {},
   "outputs": [],
   "source": [
    "barredJettisonSet = [6836,6837,6838,6839,6840]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee512b2b-4daa-4a6b-9452-e8dfdfdebc88",
   "metadata": {},
   "outputs": [],
   "source": [
    "#CHECK ON BARRED JETTISON SET BEFORE RUNNING BELOW\n",
    "print(\"the current barredJettisonSet (usually CCB's) is\",barredJettisonSet)\n",
    "for u in barredJettisonSet:\n",
    "    print(u,unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "5a6cb84c-1d0f-4f02-831c-985fe4078dc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6836, 6837, 6838, 6839, 6840] {6836, 6837, 6838, 6839, 6840}\n"
     ]
    }
   ],
   "source": [
    "origBarredJettisonSet = set(list(barredJettisonSet))\n",
    "for u in origBarredJettisonSet:\n",
    "    if unitUse[u] > 1.04:\n",
    "        barredJettisonSet.remove(u)  #this one is overused in this state\n",
    "print(barredJettisonSet, origBarredJettisonSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 2131 overPopped HDs to within 599\n",
      "working on squaring down HD 11 time is now 0\n",
      "working on squaring down HD 131 time is now 364\n",
      "working on squaring down HD 290 time is now 807\n",
      "working on squaring down HD 513 time is now 1328\n",
      "working on squaring down HD 882 time is now 1727\n",
      "working on squaring down HD 1021 time is now 1921\n",
      "working on squaring down HD 1192 time is now 2585\n",
      "working on squaring down HD 1320 time is now 2938\n",
      "working on squaring down HD 1657 time is now 3209\n",
      "working on squaring down HD 1771 time is now 3459\n",
      "working on squaring down HD 1896 time is now 3967\n",
      "working on squaring down HD 2033 time is now 4217\n",
      "working on squaring down HD 2146 time is now 4918\n",
      "working on squaring down HD 2242 time is now 5185\n",
      "working on squaring down HD 2356 time is now 5421\n",
      "working on squaring down HD 2513 time is now 5700\n",
      "working on squaring down HD 2605 time is now 5811\n",
      "working on squaring down HD 2704 time is now 6138\n",
      "working on squaring down HD 2789 time is now 7197\n",
      "working on squaring down HD 2937 time is now 7659\n",
      "working on squaring down HD 3362 time is now 8039\n",
      "working on squaring down HD 3455 time is now 8295\n",
      "working on squaring down HD 3593 time is now 8811\n",
      "working on squaring down HD 3812 time is now 9582\n",
      "working on squaring down HD 4039 time is now 10073\n",
      "working on squaring down HD 4248 time is now 10663\n",
      "working on squaring down HD 4418 time is now 11358\n",
      "working on squaring down HD 4616 time is now 11672\n",
      "working on squaring down HD 5244 time is now 11890\n",
      "working on squaring down HD 5556 time is now 12232\n",
      "working on squaring down HD 5794 time is now 12622\n",
      "working on squaring down HD 5978 time is now 13624\n",
      "working on squaring down HD 6137 time is now 14102\n",
      "working on squaring down HD 6481 time is now 14612\n",
      "working on squaring down HD 6848 time is now 14894\n",
      "working on squaring down HD 6973 time is now 15023\n",
      "We have addressed overpop in a total of 2131 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN  #new for VA, the barred set is dynamic; we stop shedding upon underuse\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))  \n",
    "barredSet = set(list(barredJettisonSet))\n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    for u in origBarredJettisonSet:\n",
    "        if unitUse[u] < 1.00:\n",
    "            barredSet = barredSet.union({u})  #adding back in when become underused (new for VA)\n",
    "    if ii%60 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        #barredSet = barredJettisonSet  #see above for VA-on modification\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c4c929d-0208-4785-aa15-5681a493a530",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "amped unit avg and sd usage are 1.01583 0.11941\n",
      "shed unit avg and sd usage are 1.00004 0.11002\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 2 out of 7059\n",
      "working on HD 673 out of 7059\n",
      "working on HD 1331 out of 7059\n",
      "working on HD 1955 out of 7059\n",
      "working on HD 2573 out of 7059\n",
      "working on HD 3210 out of 7059\n",
      "working on HD 3855 out of 7059\n",
      "working on HD 4483 out of 7059\n",
      "working on HD 5092 out of 7059\n",
      "working on HD 5713 out of 7059\n",
      "working on HD 6338 out of 7059\n",
      "working on HD 6980 out of 7059\n",
      "all done checking HD and complement contiguity for all 7059 HDs\n",
      "underpop contigFail, enclaveFail = 0 0 out of 898\n",
      "overpop contigFail, enclaveFail = 0 0 out of 2131\n",
      "total contigFail, enclaveFail =  0 0\n",
      "CCB unit 6836 with pop 13737.0 now has use 0.99789\n",
      "CCB unit 6837 with pop 169151.0 now has use 1.00754\n",
      "CCB unit 6838 with pop 171003.0 now has use 1.00326\n",
      "CCB unit 6839 with pop 92501.0 now has use 1.03193\n",
      "CCB unit 6840 with pop 51938.0 now has use 1.0265\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "#latestAvg, latestSD = getWeightedAvgAndSD(latestUnitUse,unitPop)\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "#print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "failEnclaveSet, failContigSet = set(), set()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%600 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs,5)\n",
    "    if not noEnclave:\n",
    "        noEnclave, eList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        #print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "        pass\n",
    "    if not unbroken:\n",
    "        failContigSet.add(t)\n",
    "    if not noEnclave:\n",
    "        failEnclaveSet.add(t)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")\n",
    "failContigUnderpopped, failEnclaveUnderpopped = set(underPoppedList).intersection(failContigSet), set(underPoppedList).intersection(failEnclaveSet)\n",
    "failContigOverpopped, failEnclaveOverpopped = set(overPoppedList).intersection(failContigSet), set(overPoppedList).intersection(failEnclaveSet)\n",
    "print(\"underpop contigFail, enclaveFail =\",len(failContigUnderpopped), len(failEnclaveUnderpopped),\"out of\",len(underPoppedList))\n",
    "print(\"overpop contigFail, enclaveFail =\",len(failContigOverpopped), len(failEnclaveOverpopped),\"out of\",len(overPoppedList))\n",
    "print(\"total contigFail, enclaveFail = \",len(failContigSet), len(failEnclaveSet) )\n",
    "for u in range(nUnits):\n",
    "    if abs( allUnits[u]%1 - 0.25) < 0.01:\n",
    "        print(\"CCB unit\",u,\"with pop\",unitPop[u],\"now has use\",r5(unitUse[u]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "ff3288f1-f9ca-473c-886c-ee8d6c2637bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7059 6841\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, nUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ed668f8-bf1e-46eb-963f-cf5e2b935b11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see MD code if we need to remove a stuck CCB's from any HDs and then redo the square-up after dropping them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "e7bfa674-8fc8-42c8-86e9-76d334d3c47c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "c0c3a3d8-cf79-40ad-aa2e-b6793266f1d4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "#SKIP THIS FOR STATES WITH FRAGMENTED VTD'S ###########\n",
    "print(\"prior to patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"needsEnclaveRemoval.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "7a36c0ba-5a68-445b-a223-b7fa55dfd728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 7059 HD centers\n"
     ]
    }
   ],
   "source": [
    "nHDs = len(vtdGeom)\n",
    "print(\"there are\",nHDs,\"HD centers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "1b794580-5a58-4238-b310-7c87872ed679",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\n",
      "Must have already established unitGeoms, pops, topology -- or read in via next block\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/WI7059opt3ContigGoodPop.csv ./2024state_HD_output/WI7059opt3ContigGoodPop.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999998794\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 7059 HD lists of units\n",
      "orig unit avg and sd usage are 1.00007 0.11003\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigGoodPop.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "#for t in range(nHDs):\n",
    "#    if t%500 == 0:\n",
    "#        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "#    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "#        if v in allUnits:\n",
    "#            HDunitList[t].append(allUnits.index(v))\n",
    "#    for c in unitCounties:\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(c+0.5)\n",
    "#            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "8014f0bf-74bb-40bc-b217-af4e204ea9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upon restart, need to pull in unit topology and data\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv ./state_map_files/MNunitTopologies_06Apr24.csv\n"
     ]
    }
   ],
   "source": [
    "#SKIP THE BELOW IF NOT A COLD RESTART\n",
    "print(\"upon restart, need to pull in unit topology and data\")  #note, this won't have geometries for plotting, but fine for patching\n",
    "topologyFile = \"enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv\"\n",
    "infile = input(topologyFile)\n",
    "topDF = pd.read_csv(infile)\n",
    "unitCPx, unitCPy, unitPop = topDF[\"centroid x\"], topDF[\"centroid y\"], topDF[\"unitPop\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u], unitCPy[u]) for u in range(nUnits) ]\n",
    "onBorder = topDF[\"onBorder\"]\n",
    "borderSet = set()\n",
    "for i, onB in enumerate(onBorder):\n",
    "    if onB == 1:\n",
    "        borderSet.add(i)\n",
    "borderList = list(borderSet)\n",
    "\n",
    "nbrListString = topDF[\"neighborList\"]\n",
    "unitNbrs = [ast.literal_eval(nbrListString[u]) for u in range(nUnits)]\n",
    "unitParentVTDno = topDF[\"unitParentVTDno\"]  #NOTE: some units are VTD fragments, so they share a parentVTDno\n",
    "uVLstring = topDF[\"unitVTDlist\"]\n",
    "unitNbrs = [ast.literal_eval(uVLstring[u]) for u in range(nUnits)]\n",
    "allUnits = topDF[\"allUnits\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5f3a5392-11f1-4061-a458-aecd834b2748",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working avg precinct-to-HDcP distance for HD 0\n",
      "working avg precinct-to-HDcP distance for HD 800\n",
      "working avg precinct-to-HDcP distance for HD 1600\n",
      "working avg precinct-to-HDcP distance for HD 2400\n",
      "working avg precinct-to-HDcP distance for HD 3200\n",
      "working avg precinct-to-HDcP distance for HD 4000\n",
      "working avg precinct-to-HDcP distance for HD 4800\n",
      "working avg precinct-to-HDcP distance for HD 5600\n",
      "working avg precinct-to-HDcP distance for HD 6400\n",
      "all avgDist to HD centers computed\n"
     ]
    }
   ],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working avg precinct-to-HDcP distance for HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ea0db02f-9df8-4906-acb4-086c29c0fcc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "checking for discontiguities for HD 5000\n",
      "checking for discontiguities for HD 5500\n",
      "checking for discontiguities for HD 6000\n",
      "checking for discontiguities for HD 6500\n",
      "checking for discontiguities for HD 7000\n",
      "out of 6678 total HDs, there were 6678 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking unitUse, pop for county clusters\n",
      "6836 0.99792 13737.0\n",
      "6837 1.00757 169151.0\n",
      "6838 1.0033 171003.0\n",
      "6839 1.03195 92501.0\n",
      "6840 1.02654 51938.0\n"
     ]
    }
   ],
   "source": [
    "print(\"checking unitUse, pop for county clusters\")\n",
    "for uNo in allUnits:\n",
    "    if uNo - int(uNo) > 0.23 and uNo - int(uNo) < 0.27:\n",
    "        u = allUnits.index(uNo)\n",
    "        print(u,r5(unitUse[u]), unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5f9ca091-1eb6-4135-a233-7f5ae0f5e3d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... for restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc95ca58-c27f-4ac9-b6f7-234a94945f07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e9dd457d-fb37-49cf-9b19-19c17c328ede",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.07\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 1514 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 200\n",
      "enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97 0.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 2294 units out of 6841 with usage below 0.97\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10 5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 36835\n",
      "current avg and SD of unit usage are 1.00007 0.11003 . Now trying to increase up to 200 units' underusage\n",
      "all done trying to increase usage of unit 1574 final usage = 0.97038 10377 sec elapsed 293 0 successful, failed patches, couldn't start= 92\n",
      "current avg and SD of usage are 1.00009 0.10612\n",
      "all done trying to increase usage of unit 6768 final usage = 0.73414 12093 sec elapsed 34 0 successful, failed patches, couldn't start= 33\n",
      "current avg and SD of usage are 1.00009 0.10576\n",
      "all done trying to increase usage of unit 6779 final usage = 0.75 15718 sec elapsed 43 0 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00009 0.10529\n",
      "all done trying to increase usage of unit 3153 final usage = 0.72441 16174 sec elapsed 10 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.0001 0.10522\n",
      "begin usage increase for unit 3192 with usage 0.72012 . Sec, total UU units tried = 16176 5\n",
      "all done trying to increase usage of unit 3192 final usage = 0.77485 19005 sec elapsed 62 0 successful, failed patches, couldn't start= 57\n",
      "current avg and SD of usage are 1.00009 0.10467\n",
      "all done trying to increase usage of unit 3164 final usage = 0.73525 19734 sec elapsed 17 0 successful, failed patches, couldn't start= 28\n",
      "current avg and SD of usage are 1.00009 0.10458\n",
      "all done trying to increase usage of unit 3186 final usage = 0.74664 21844 sec elapsed 30 0 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00009 0.10433\n",
      "all done trying to increase usage of unit 1690 final usage = 0.75708 24278 sec elapsed 39 0 successful, failed patches, couldn't start= 106\n",
      "current avg and SD of usage are 1.00009 0.104\n",
      "all done trying to increase usage of unit 3354 final usage = 0.75439 25565 sec elapsed 30 0 successful, failed patches, couldn't start= 48\n",
      "current avg and SD of usage are 1.00009 0.10386\n",
      "begin usage increase for unit 3353 with usage 0.72807 . Sec, total UU units tried = 25567 10\n",
      "all done trying to increase usage of unit 3353 final usage = 0.77154 28339 sec elapsed 39 0 successful, failed patches, couldn't start= 54\n",
      "current avg and SD of usage are 1.0001 0.1034\n",
      "all done trying to increase usage of unit 6762 final usage = 0.76651 33429 sec elapsed 45 0 successful, failed patches, couldn't start= 43\n",
      "current avg and SD of usage are 1.0001 0.10309\n",
      "all done trying to increase usage of unit 3225 final usage = 0.75193 35513 sec elapsed 22 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.0001 0.10296\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[37], line 142\u001b[0m\n\u001b[0;32m    140\u001b[0m     \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[0;32m    141\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m excess \u001b[38;5;241m-\u001b[39m unitPop[shedU] \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m*\u001b[39mmaxGap:\n\u001b[1;32m--> 142\u001b[0m     contig,cContig, __, ___ \u001b[38;5;241m=\u001b[39m \u001b[43menclaveCheck\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtrySet\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdifference\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[43mshedU\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    143\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m contig \u001b[38;5;129;01mand\u001b[39;00m cContig:\n\u001b[0;32m    144\u001b[0m         notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 723\u001b[0m, in \u001b[0;36menclaveCheck\u001b[1;34m(UNITLIST, UNITNBRS, maxLoops)\u001b[0m\n\u001b[0;32m    720\u001b[0m \u001b[38;5;66;03m#adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\u001b[39;00m\n\u001b[0;32m    721\u001b[0m \u001b[38;5;66;03m#BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\u001b[39;00m\n\u001b[0;32m    722\u001b[0m BDRYLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m (\u001b[38;5;28mset\u001b[39m(get2nbrs(ADJLIST,UNITNBRS))\u001b[38;5;241m.\u001b[39mintersection(UNITSET) )  \u001b[38;5;66;03m#in case inHD boundary is only queen-adjacent\u001b[39;00m\n\u001b[1;32m--> 723\u001b[0m noEnclave, enclaveList \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mUNITNBRS\u001b[49m\u001b[43m)\u001b[49m  \n\u001b[0;32m    724\u001b[0m unbroken, smallPieceList \u001b[38;5;241m=\u001b[39m isContiguous(BDRYLIST, UNITNBRS)\n\u001b[0;32m    725\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m unbroken: \u001b[38;5;66;03m#could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "\n",
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overused first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "fd36caf6-71e4-44a4-9d09-7469512c5e05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.06\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 1633 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 120\n",
      "enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97 0.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 2228 units out of 6841 with usage below 0.97\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10 10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 36835\n",
      "current avg and SD of unit usage are 1.00011 0.10011 . Now trying to increase up to 120 units' underusage\n",
      "all done trying to increase usage of unit 6768 final usage = 0.76677 1076 sec elapsed 40 49 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09988\n",
      "all done trying to increase usage of unit 6772 final usage = 0.88713 2733 sec elapsed 165 8 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00012 0.09853\n",
      "all done trying to increase usage of unit 3153 final usage = 0.75285 3008 sec elapsed 16 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00012 0.09846\n",
      "all done trying to increase usage of unit 3170 final usage = 0.8032 3643 sec elapsed 60 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00012 0.09797\n",
      "all done trying to increase usage of unit 3328 final usage = 0.79463 4785 sec elapsed 64 56 successful, failed patches, couldn't start= 21\n",
      "current avg and SD of usage are 1.00011 0.09749\n",
      "all done trying to increase usage of unit 3176 final usage = 0.79777 5857 sec elapsed 65 28 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09712\n",
      "all done trying to increase usage of unit 1681 final usage = 0.83037 7771 sec elapsed 102 43 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09678\n",
      "all done trying to increase usage of unit 3164 final usage = 0.75979 8563 sec elapsed 11 41 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09674\n",
      "all done trying to increase usage of unit 6779 final usage = 0.78626 9218 sec elapsed 43 5 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00011 0.09659\n",
      "begin usage increase for unit 3137 with usage 0.75567 . Sec, total UU units tried = 9221 10\n",
      "all done trying to increase usage of unit 3137 final usage = 0.8178 11138 sec elapsed 69 88 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09632\n",
      "all done trying to increase usage of unit 1566 final usage = 0.97035 12608 sec elapsed 244 8 successful, failed patches, couldn't start= 25\n",
      "current avg and SD of usage are 1.00011 0.09403\n",
      "all done trying to increase usage of unit 3223 final usage = 0.76471 13480 sec elapsed 5 46 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00011 0.09399\n",
      "all done trying to increase usage of unit 4120 final usage = 0.97028 14063 sec elapsed 148 10 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.09104\n",
      "all done trying to increase usage of unit 3165 final usage = 0.76348 14894 sec elapsed 4 42 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.09102\n",
      "all done trying to increase usage of unit 3186 final usage = 0.81747 15720 sec elapsed 53 11 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00014 0.09074\n",
      "all done trying to increase usage of unit 3149 final usage = 0.86845 17864 sec elapsed 133 16 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.09042\n",
      "all done trying to increase usage of unit 3354 final usage = 0.81047 18952 sec elapsed 49 31 successful, failed patches, couldn't start= 32\n",
      "current avg and SD of usage are 1.00014 0.0902\n",
      "all done trying to increase usage of unit 4958 final usage = 0.93826 20590 sec elapsed 178 29 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08808\n",
      "all done trying to increase usage of unit 1661 final usage = 0.78803 20832 sec elapsed 26 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08798\n",
      "begin usage increase for unit 4116 with usage 0.76995 . Sec, total UU units tried = 20834 20\n",
      "all done trying to increase usage of unit 4116 final usage = 0.97123 21577 sec elapsed 139 1 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00013 0.08587\n",
      "all done trying to increase usage of unit 3225 final usage = 0.80817 22161 sec elapsed 39 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00013 0.08564\n",
      "all done trying to increase usage of unit 1684 final usage = 0.79307 23857 sec elapsed 35 77 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00013 0.08554\n",
      "all done trying to increase usage of unit 1660 final usage = 0.97087 26444 sec elapsed 257 31 successful, failed patches, couldn't start= 34\n",
      "current avg and SD of usage are 1.00014 0.08437\n",
      "all done trying to increase usage of unit 1939 final usage = 0.92952 29780 sec elapsed 212 54 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08375\n",
      "all done trying to increase usage of unit 3228 final usage = 0.81276 31413 sec elapsed 43 60 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08359\n",
      "all done trying to increase usage of unit 2570 final usage = 0.93746 34104 sec elapsed 216 5 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08302\n",
      "all done trying to increase usage of unit 1690 final usage = 0.82128 35749 sec elapsed 67 60 successful, failed patches, couldn't start= 94\n",
      "current avg and SD of usage are 1.00014 0.08278\n",
      "all done trying to increase usage of unit 6762 final usage = 0.81088 37989 sec elapsed 54 97 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00014 0.08263\n",
      "all done trying to increase usage of unit 1691 final usage = 0.89642 40332 sec elapsed 169 34 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08237\n",
      "begin usage increase for unit 3353 with usage 0.77738 . Sec, total UU units tried = 40335 30\n",
      "all done trying to increase usage of unit 3353 final usage = 0.81579 41871 sec elapsed 45 49 successful, failed patches, couldn't start= 51\n",
      "current avg and SD of usage are 1.00014 0.08226\n",
      "all done trying to increase usage of unit 6627 final usage = 0.84648 44007 sec elapsed 65 137 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00014 0.08166\n",
      "all done trying to increase usage of unit 2557 final usage = 0.96626 46502 sec elapsed 191 26 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.0802\n",
      "all done trying to increase usage of unit 3161 final usage = 0.91269 49256 sec elapsed 180 13 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07997\n",
      "all done trying to increase usage of unit 1947 final usage = 0.81783 50717 sec elapsed 56 61 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07979\n",
      "all done trying to increase usage of unit 1643 final usage = 0.9703 55163 sec elapsed 239 164 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07885\n",
      "all done trying to increase usage of unit 1654 final usage = 0.97011 58601 sec elapsed 206 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.0785\n",
      "all done trying to increase usage of unit 3938 final usage = 0.96193 62300 sec elapsed 231 20 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07802\n",
      "all done trying to increase usage of unit 1936 final usage = 0.8141 66258 sec elapsed 31 258 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07779\n",
      "all done trying to increase usage of unit 3332 final usage = 0.80152 67145 sec elapsed 26 34 successful, failed patches, couldn't start= 78\n",
      "current avg and SD of usage are 1.00015 0.07774\n",
      "begin usage increase for unit 1948 with usage 0.78567 . Sec, total UU units tried = 67148 40\n",
      "all done trying to increase usage of unit 1948 final usage = 0.96353 71676 sec elapsed 227 70 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07742\n",
      "all done trying to increase usage of unit 1943 final usage = 0.97062 75293 sec elapsed 213 7 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07718\n",
      "all done trying to increase usage of unit 6565 final usage = 0.93528 78058 sec elapsed 168 35 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07599\n",
      "all done trying to increase usage of unit 6769 final usage = 0.81554 78823 sec elapsed 36 25 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.0759\n",
      "all done trying to increase usage of unit 1953 final usage = 0.81595 79680 sec elapsed 38 30 successful, failed patches, couldn't start= 146\n",
      "current avg and SD of usage are 1.00015 0.07579\n",
      "all done trying to increase usage of unit 1938 final usage = 0.96477 82955 sec elapsed 218 3 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00015 0.07557\n",
      "all done trying to increase usage of unit 6767 final usage = 0.92031 85991 sec elapsed 170 42 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00016 0.07539\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[44], line 107\u001b[0m\n\u001b[0;32m    105\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[ij]   \u001b[38;5;66;03m#work from low to high score\u001b[39;00m\n\u001b[0;32m    106\u001b[0m addU \u001b[38;5;241m=\u001b[39m addCandidates[listNo]\n\u001b[1;32m--> 107\u001b[0m cContig \u001b[38;5;241m=\u001b[39m \u001b[43mavoidedEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtrySet\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43maddU\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    108\u001b[0m \u001b[38;5;66;03m#cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\u001b[39;00m\n\u001b[0;32m    109\u001b[0m \u001b[38;5;66;03m#contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\u001b[39;00m\n\u001b[0;32m    110\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cContig: \u001b[38;5;66;03m#contig and cContig:\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[43], line 766\u001b[0m, in \u001b[0;36mavoidedEnclave\u001b[1;34m(UNITLIST, UNITNBRS, ADDLIST, MAXLOOPS)\u001b[0m\n\u001b[0;32m    764\u001b[0m newFoundSet \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m()\n\u001b[0;32m    765\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m U \u001b[38;5;129;01min\u001b[39;00m lastFoundSet:\n\u001b[1;32m--> 766\u001b[0m     newFoundSet \u001b[38;5;241m=\u001b[39m newFoundSet\u001b[38;5;241m.\u001b[39munion(\u001b[38;5;28;43mset\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mUNITNBRS\u001b[49m\u001b[43m[\u001b[49m\u001b[43mU\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m    767\u001b[0m newFoundSet \u001b[38;5;241m=\u001b[39m newFoundSet\u001b[38;5;241m.\u001b[39mdifference(willBeInUnitSet)\n\u001b[0;32m    769\u001b[0m foundTotalSet \u001b[38;5;241m=\u001b[39m foundTotalSet\u001b[38;5;241m.\u001b[39munion(newFoundSet)\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#NEW for WI - faster(?) alternative to above, use the avoidedEnclave, avoidedIsland subroutines vs. wontEnclave\n",
    "\n",
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overused first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used.  Using new-for-WI avoidedEnclave routines\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency; e.g. 10\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        complementContig = avoidedEnclave(HDunitList[t], unitNbrs, UUUc)\n",
    "        #contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not complementContig: #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            complementContig  = avoidedEnclave(HDunitList[t], unitNbrs, [UUU])\n",
    "            loopUUUc = [UUU]\n",
    "        if complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = avoidedEnclave(list(trySet), unitNbrs, [addU])\n",
    "                    #cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig = avoidedIsland(list(trySet), unitNbrs, [shedU])\n",
    "                        #contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig: # and contig :\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "622f22cd-1247-4665-ad60-72baace563ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for WI, stopped at ~0.075 here to work on other calcns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00004 1.00012 and their SDs are 0.11002 0.07531\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 500 out of 7059\n",
      "working on HD 1000 out of 7059\n",
      "working on HD 1500 out of 7059\n",
      "working on HD 2000 out of 7059\n",
      "working on HD 2500 out of 7059\n",
      "working on HD 3000 out of 7059\n",
      "working on HD 3500 out of 7059\n",
      "working on HD 4000 out of 7059\n",
      "working on HD 4500 out of 7059\n",
      "working on HD 5000 out of 7059\n",
      "working on HD 5500 out of 7059\n",
      "working on HD 6000 out of 7059\n",
      "working on HD 6500 out of 7059\n",
      "working on HD 7000 out of 7059\n",
      "all done checking HD and complement contiguity for all 7059 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1ee72cf0-618e-411f-aa37-518ac2c679ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"underPatched.csv\" #\"contigUnpatchedB.csv\"  #underPatched\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "d630bc3f-ab64-485a-87e1-d9384284c595",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\n",
      "Must have already established unitGeoms, pops, topology -- or read in via next block\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/WI7059underPatched.csv ./2024state_HD_output/WI7059underPatched.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999998963\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 7059 HD lists of units\n",
      "read-in unit avg and sd usage are 1.00016 0.07532\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"underPatched.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "#for t in range(nHDs):\n",
    "#    if t%500 == 0:\n",
    "#        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "#    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "#        if v in allUnits:\n",
    "#            HDunitList[t].append(allUnits.index(v))\n",
    "#    for c in unitCounties:\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(c+0.5)\n",
    "#            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"read-in unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "77c07848-50c2-4fe9-8841-768b02bf4ac4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.03\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 2126 units out of 6841 with usage above 1.03\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 36835\n",
      "current avg and SD of unit usage are 1.00016 0.07532 . Now trying to reduce up to 2126 units' overusage\n",
      "starting to reduce usage for unit 424 with usage 1.31763 . Total units tried = 1\n",
      "try to drop unit 424 from 49 th HD.  usage down to 1.2741919447112668\n",
      "try to drop unit 424 from 98 th HD.  usage down to 1.2289464816606084\n",
      "try to drop unit 424 from 147 th HD.  usage down to 1.1503108903411736\n",
      "try to drop unit 424 from 196 th HD.  usage down to 1.07497101150747\n",
      "try to drop unit 424 from 245 th HD.  usage down to 1.035364094447643\n",
      "all done trying to reduce usage of unit 424 final usage = 1.03244 204 sec elapsed 172 4 successful, failed patches, couldn't start= 71\n",
      "current avg and SD of usage are 1.00009 0.06886\n",
      "starting to reduce usage for unit 1365 with usage 1.37336 . Total units tried = 2\n",
      "try to drop unit 1365 from 46 th HD.  usage down to 1.3251221045866808\n",
      "try to drop unit 1365 from 92 th HD.  usage down to 1.3006078675634616\n",
      "try to drop unit 1365 from 138 th HD.  usage down to 1.2687393594332756\n",
      "try to drop unit 1365 from 184 th HD.  usage down to 1.2557913357918289\n",
      "try to drop unit 1365 from 230 th HD.  usage down to 1.2369509365735438\n",
      "all done trying to reduce usage of unit 1365 final usage = 1.23695 870 sec elapsed 98 1 successful, failed patches, couldn't start= 131\n",
      "current avg and SD of usage are 1.00008 0.06636\n",
      "starting to reduce usage for unit 128 with usage 1.26665 . Total units tried = 3\n",
      "try to drop unit 128 from 70 th HD.  usage down to 1.2165088319460968\n",
      "try to drop unit 128 from 140 th HD.  usage down to 1.1413318384082367\n",
      "try to drop unit 128 from 210 th HD.  usage down to 1.0720716532415926\n",
      "all done trying to reduce usage of unit 128 final usage = 1.02961 1733 sec elapsed 144 5 successful, failed patches, couldn't start= 95\n",
      "current avg and SD of usage are 1.00009 0.06248\n",
      "starting to reduce usage for unit 125 with usage 1.26055 . Total units tried = 4\n",
      "try to drop unit 125 from 54 th HD.  usage down to 1.2005637188612845\n",
      "try to drop unit 125 from 108 th HD.  usage down to 1.162280244830121\n",
      "try to drop unit 125 from 162 th HD.  usage down to 1.1466799056214925\n",
      "try to drop unit 125 from 216 th HD.  usage down to 1.127496089904488\n",
      "try to drop unit 125 from 270 th HD.  usage down to 1.108794143187664\n",
      "all done trying to reduce usage of unit 125 final usage = 1.10841 2162 sec elapsed 91 0 successful, failed patches, couldn't start= 183\n",
      "current avg and SD of usage are 1.00008 0.06042\n",
      "starting to reduce usage for unit 1155 with usage 1.23225 . Total units tried = 5\n",
      "try to drop unit 1155 from 62 th HD.  usage down to 1.145638797105691\n",
      "try to drop unit 1155 from 124 th HD.  usage down to 1.0718123941458004\n",
      "all done trying to reduce usage of unit 1155 final usage = 1.02963 2884 sec elapsed 130 20 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00009 0.05819\n",
      "starting to reduce usage for unit 1714 with usage 1.23207 . Total units tried = 6\n",
      "try to drop unit 1714 from 91 th HD.  usage down to 1.164669229169174\n",
      "try to drop unit 1714 from 182 th HD.  usage down to 1.114584715454743\n",
      "try to drop unit 1714 from 273 th HD.  usage down to 1.0835252042938741\n",
      "all done trying to reduce usage of unit 1714 final usage = 1.03 4388 sec elapsed 217 0 successful, failed patches, couldn't start= 126\n",
      "current avg and SD of usage are 1.00009 0.05615\n",
      "starting to reduce usage for unit 4043 with usage 1.20202 . Total units tried = 7\n",
      "try to drop unit 4043 from 61 th HD.  usage down to 1.1311949434974164\n",
      "try to drop unit 4043 from 122 th HD.  usage down to 1.087783297402374\n",
      "try to drop unit 4043 from 183 th HD.  usage down to 1.0420220309149066\n",
      "all done trying to reduce usage of unit 4043 final usage = 1.028 4531 sec elapsed 121 0 successful, failed patches, couldn't start= 85\n",
      "current avg and SD of usage are 1.00007 0.05296\n",
      "starting to reduce usage for unit 1383 with usage 1.23695 . Total units tried = 8\n",
      "try to drop unit 1383 from 24 th HD.  usage down to 1.1949373892677506\n",
      "try to drop unit 1383 from 48 th HD.  usage down to 1.164518560270501\n",
      "try to drop unit 1383 from 72 th HD.  usage down to 1.142169340304428\n",
      "try to drop unit 1383 from 96 th HD.  usage down to 1.1192880283719575\n",
      "try to drop unit 1383 from 120 th HD.  usage down to 1.1011507506806935\n",
      "all done trying to reduce usage of unit 1383 final usage = 1.09846 5075 sec elapsed 116 5 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00008 0.05074\n",
      "starting to reduce usage for unit 2317 with usage 1.1999 . Total units tried = 9\n",
      "try to drop unit 2317 from 62 th HD.  usage down to 1.1290204247981592\n",
      "try to drop unit 2317 from 124 th HD.  usage down to 1.0890877371466599\n",
      "try to drop unit 2317 from 186 th HD.  usage down to 1.0480759344102502\n",
      "all done trying to reduce usage of unit 2317 final usage = 1.02963 6241 sec elapsed 194 0 successful, failed patches, couldn't start= 24\n",
      "current avg and SD of usage are 1.00008 0.04968\n",
      "starting to reduce usage for unit 5409 with usage 1.18608 . Total units tried = 10\n",
      "try to drop unit 5409 from 65 th HD.  usage down to 1.1707923589149711\n",
      "try to drop unit 5409 from 130 th HD.  usage down to 1.1628123367965055\n",
      "try to drop unit 5409 from 195 th HD.  usage down to 1.153944589815738\n",
      "try to drop unit 5409 from 260 th HD.  usage down to 1.149687854084575\n",
      "try to drop unit 5409 from 325 th HD.  usage down to 1.1457704627197358\n",
      "all done trying to reduce usage of unit 5409 final usage = 1.14517 6369 sec elapsed 30 0 successful, failed patches, couldn't start= 299\n",
      "current avg and SD of usage are 1.00008 0.04909\n",
      "starting to reduce usage for unit 5381 with usage 1.18296 . Total units tried = 11\n",
      "try to drop unit 5381 from 53 th HD.  usage down to 1.1180568870108203\n",
      "try to drop unit 5381 from 106 th HD.  usage down to 1.0580445145152286\n",
      "all done trying to reduce usage of unit 5381 final usage = 1.02731 6487 sec elapsed 77 1 successful, failed patches, couldn't start= 64\n",
      "current avg and SD of usage are 1.00007 0.04702\n",
      "starting to reduce usage for unit 1879 with usage 1.19065 . Total units tried = 12\n",
      "try to drop unit 1879 from 83 th HD.  usage down to 1.1262703780533845\n",
      "try to drop unit 1879 from 166 th HD.  usage down to 1.063788935948418\n",
      "all done trying to reduce usage of unit 1879 final usage = 1.0288 7515 sec elapsed 163 0 successful, failed patches, couldn't start= 63\n",
      "current avg and SD of usage are 1.00007 0.04584\n",
      "starting to reduce usage for unit 5398 with usage 1.14517 . Total units tried = 13\n",
      "try to drop unit 5398 from 38 th HD.  usage down to 1.0715924989963304\n",
      "all done trying to reduce usage of unit 5398 final usage = 1.02882 7623 sec elapsed 60 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00006 0.04458\n",
      "starting to reduce usage for unit 1334 with usage 1.15182 . Total units tried = 14\n",
      "try to drop unit 1334 from 54 th HD.  usage down to 1.057482560244617\n",
      "all done trying to reduce usage of unit 1334 final usage = 1.02916 7751 sec elapsed 68 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00007 0.04321\n",
      "starting to reduce usage for unit 1284 with usage 1.1316 . Total units tried = 15\n",
      "try to drop unit 1284 from 58 th HD.  usage down to 1.1297086151729676\n",
      "try to drop unit 1284 from 116 th HD.  usage down to 1.125810227092643\n",
      "try to drop unit 1284 from 174 th HD.  usage down to 1.1251871908360722\n",
      "try to drop unit 1284 from 232 th HD.  usage down to 1.1141001316995498\n",
      "try to drop unit 1284 from 290 th HD.  usage down to 1.1097931730021704\n",
      "all done trying to reduce usage of unit 1284 final usage = 1.10979 7968 sec elapsed 21 0 successful, failed patches, couldn't start= 270\n",
      "current avg and SD of usage are 1.00007 0.04311\n",
      "starting to reduce usage for unit 2912 with usage 1.12239 . Total units tried = 16\n",
      "try to drop unit 2912 from 36 th HD.  usage down to 1.1169546965090595\n",
      "try to drop unit 2912 from 72 th HD.  usage down to 1.1157832797565108\n",
      "try to drop unit 2912 from 108 th HD.  usage down to 1.1112618554196154\n",
      "try to drop unit 2912 from 144 th HD.  usage down to 1.1073661820942193\n",
      "try to drop unit 2912 from 180 th HD.  usage down to 1.1019095246837345\n",
      "all done trying to reduce usage of unit 2912 final usage = 1.10048 8044 sec elapsed 24 0 successful, failed patches, couldn't start= 157\n",
      "current avg and SD of usage are 1.00006 0.04266\n",
      "starting to reduce usage for unit 1703 with usage 1.12995 . Total units tried = 17\n",
      "try to drop unit 1703 from 50 th HD.  usage down to 1.0948810241685267\n",
      "try to drop unit 1703 from 100 th HD.  usage down to 1.0699297116014836\n",
      "try to drop unit 1703 from 150 th HD.  usage down to 1.0511721124085773\n",
      "try to drop unit 1703 from 200 th HD.  usage down to 1.0392407644886346\n",
      "all done trying to reduce usage of unit 1703 final usage = 1.02989 8965 sec elapsed 135 0 successful, failed patches, couldn't start= 94\n",
      "current avg and SD of usage are 1.00006 0.04223\n",
      "starting to reduce usage for unit 1321 with usage 1.10979 . Total units tried = 18\n",
      "try to drop unit 1321 from 33 th HD.  usage down to 1.0678162748879405\n",
      "try to drop unit 1321 from 66 th HD.  usage down to 1.0333782512159546\n",
      "all done trying to reduce usage of unit 1321 final usage = 1.02958 9218 sec elapsed 63 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00005 0.04108\n",
      "starting to reduce usage for unit 6803 with usage 1.10821 . Total units tried = 19\n",
      "try to drop unit 6803 from 69 th HD.  usage down to 1.07253451895735\n",
      "try to drop unit 6803 from 138 th HD.  usage down to 1.0492079872162663\n",
      "try to drop unit 6803 from 207 th HD.  usage down to 1.0381141411924117\n",
      "try to drop unit 6803 from 276 th HD.  usage down to 1.0333307430047143\n",
      "try to drop unit 6803 from 345 th HD.  usage down to 1.0317439687477854\n",
      "all done trying to reduce usage of unit 6803 final usage = 1.03051 9838 sec elapsed 84 0 successful, failed patches, couldn't start= 262\n",
      "current avg and SD of usage are 1.00005 0.04061\n",
      "starting to reduce usage for unit 371 with usage 1.10794 . Total units tried = 20\n",
      "try to drop unit 371 from 36 th HD.  usage down to 1.053930303417929\n",
      "all done trying to reduce usage of unit 371 final usage = 1.02946 9932 sec elapsed 39 0 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00004 0.03985\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  using 5/24/24 new avoidedIsland method\n",
    "maxSD = 0.04 #0.06  #0.08  #0.04\n",
    "stopMaxUse = 1.03  #1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "#maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "#maxNtries = 10 #overrirde\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OUUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists) #work from farthest HD in\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig = avoidedIsland(HDunitList[t], unitNbrs, set(OUUc))\n",
    "        #contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not contig:\n",
    "        #if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                #trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "                contig = avoidedIsland(HDunitList[t], unitNbrs, set([OUU]))\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig: # and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    contig = avoidedIsland(list(trySet), unitNbrs, set([shedU]))\n",
    "                    if contig: #and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative)  #NEW FOR GA 3/11/24\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...  \n",
    "                    #canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    canAdd = avoidedEnclave(list(trySet), unitNbrs, [unitNoToAdd])\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= 2.* maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "            \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92f90621-e7fc-4891-a5cd-69033c3c48e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#copy one of two above blocks and run again if needed (n/a for NC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "cb60da52-ca13-45dd-8bf0-475213183a0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "underused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"overused units\")\n",
    "maxPlot = 1.06\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > maxPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"underused units\")\n",
    "minPlot = 0.94\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "0d4f1372-6044-4803-91d9-de4b95a40083",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00004 1.0 and their SDs are 0.11002 0.03985\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 300 out of 7059\n",
      "working on HD 600 out of 7059\n",
      "working on HD 900 out of 7059\n",
      "working on HD 1200 out of 7059\n",
      "working on HD 1500 out of 7059\n",
      "working on HD 1800 out of 7059\n",
      "working on HD 2100 out of 7059\n",
      "working on HD 2400 out of 7059\n",
      "working on HD 2700 out of 7059\n",
      "working on HD 3000 out of 7059\n",
      "working on HD 3300 out of 7059\n",
      "working on HD 3600 out of 7059\n",
      "working on HD 3900 out of 7059\n",
      "working on HD 4200 out of 7059\n",
      "working on HD 4500 out of 7059\n",
      "working on HD 5100 out of 7059\n",
      "working on HD 5400 out of 7059\n",
      "working on HD 5700 out of 7059\n",
      "working on HD 6000 out of 7059\n",
      "working on HD 6300 out of 7059\n",
      "working on HD 6600 out of 7059\n",
      "working on HD 6900 out of 7059\n",
      "all done checking HD and complement contiguity for all 7059 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "ac9cd133-94f0-494b-ac74-0c584482d97e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"fullyPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "26b87c95-101f-4f8f-bb73-feb1827ac6b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    }
   ],
   "source": [
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))\n",
    "if noFrag == 1:\n",
    "    nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ec102553-e4f3-4010-86bc-725a01b95788",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([v for v in range(len(parentVTDno))],parentVTDno)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "55d64c64-b473-49d0-b863-d4123cbb9b6c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "confirming vtd 0 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 2000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 4000 is not in the map but missing from the parent vtd list\n",
      "confirming vtd 6000 is not in the map but missing from the parent vtd list\n"
     ]
    }
   ],
   "source": [
    "for v in range(nVTDs):\n",
    "    if v %2000 == 0:\n",
    "        print(\"confirming vtd\",v,\"is not in the map but missing from the parent vtd list\")\n",
    "    if MAP.contains(vtdGeom[v].centroid) and v not in parentVTDno:\n",
    "        print(\"Uhoh,\",v,\"is in the map but not in the parent vtd list\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "working on full or partial VTD master list for unit 4000\n",
      "working on full or partial VTD master list for unit 6000\n",
      "Now converting unit lists to vtd lists for all HDs\n"
     ]
    }
   ],
   "source": [
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "                                    \n",
    "HDpartialVTDlist, HDfullVTDlist, HDvtdFrac = [list() for t in range(nHDs)] ,[list() for t in range(nHDs)],[list() for t in range(nHDs)]               \n",
    "print(\"Now converting unit lists to vtd lists for all HDs\")\n",
    "if noFrag == 1:\n",
    "    for t in popHDlist:\n",
    "        for u in HDunitList[t]:\n",
    "            vtdList[t] += unitVTDlist[u]\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "else:\n",
    "    for t in popHDlist:\n",
    "        partialList, partialFrac = list(), list()  #for many HDs, we'll recover whole VTDs when aggregating units\n",
    "        for u in HDunitList[t]:\n",
    "            HDfullVTDlist[t] +=   unitFullVTDlist[u] \n",
    "            partialList +=         unitPartialVTDlist[u]\n",
    "            partialFrac +=          unitVTDfrac[u]\n",
    "        partialSet = set(partialList)  #non-duplicated set of partials across the HD, prepping to aggregate where possible\n",
    "        partialSetFrac, partialSetList = [0. for v in partialSet], list(partialSet)\n",
    "        for i,v in enumerate(partialList):\n",
    "            partialSetFrac[partialSetList.index(v)] += partialFrac[i]\n",
    "        for i,v in enumerate(partialSetList):\n",
    "            if partialSetFrac[i] > 0.999:  #the district has all the fragments of the original VTD contained in the HD's units\n",
    "                HDfullVTDlist[t].append(v)\n",
    "            else:\n",
    "                HDpartialVTDlist[t].append(v)\n",
    "                HDvtdFrac[t].append(      r5(partialSetFrac[i]) )  #save the aggregated fraction of this VTD across all units\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5075814f-4a75-4807-ad8d-b3cc969cb470",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7059 7059 7059 7059 7059 7059\n"
     ]
    }
   ],
   "source": [
    "\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDvPop = HDvPop[0:nHDs]\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDfullVTDlist = HDfullVTDlist[0:nHDs]\n",
    "HDpartialVTDlist = HDpartialVTDlist[0:nHDs]\n",
    "HDvtdFrac = HDvtdFrac[0:nHDs]\n",
    "hdCPx, hdCPy = hdCPx[0:nHDs], hdCPy[0:nHDs]\n",
    "print(nHDs,len(tList), len(HDweight), len(HDvPop), len(HDvtdFrac), len(hdCPx) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e385f357-5b7e-46f5-b054-c5c38d799395",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 7059\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight), nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "8d922813-2854-41d7-9405-22db5d5d5a59",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now append the cut districts and adjust the HDweights\n",
      "8 0 are the number of HD-drawn and cut districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Now append the cut districts and adjust the HDweights\")\n",
    "print(nDistricts,nCutDistricts,\"are the number of HD-drawn and cut districts\")\n",
    "HDweight = [nDistricts/float(nCutDistricts + nDistricts) * HDweight[t] for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "if type(hdCPx) != type(list()):\n",
    "    hdCPx, hdCPy = hdCPx.to_list(), hdCPy.to_list()\n",
    "for L in allCutLists:\n",
    "    tList.append(len(tList))\n",
    "    HDweight.append(1./(nCutDistricts + nDistricts))\n",
    "    pop = np.sum([tractPop[v] for v in L])\n",
    "    HDvPop.append(pop )\n",
    "    HDfullVTDlist.append(L)\n",
    "    HDpartialVTDlist.append(list() )\n",
    "    HDvtdFrac.append(list() )\n",
    "    hdCPx.append(np.sum([tractPop[v]*tractCPx[v] for v in L]) / pop )\n",
    "    hdCPy.append(np.sum([tractPop[v]*tractCPy[v] for v in L]) / pop )\n",
    "    \n",
    "\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                        \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedWithCutsVTDs.csv\"   #patchedWithCutsVTDs  #patchedVTDs\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "b0b611f7-6c35-495d-b38c-c848317d63ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "b9d808de-119f-4197-8e0c-8407c105d789",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that VTDs are represented 1.0 across all units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"checking that VTDs are represented 1.0 across all units\")\n",
    "vtdUSE = [0. for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        vtdUSE[v] += 1\n",
    "    for i,v in enumerate(unitPartialVTDlist[u]):\n",
    "        vtdUSE[v] += unitVTDfrac[u][i]\n",
    "plotVTDs, plotUses = list(), list()\n",
    "for v in range(nVTDs):\n",
    "    if tractPop[v] > 0  and v not in allCutVTDs:\n",
    "        plotVTDs.append(v)\n",
    "        plotUses.append(vtdUSE[v])\n",
    "plt.scatter(plotVTDs, plotUses)\n",
    "plt.show()\n",
    "for i,v in enumerate(plotVTDs):\n",
    "    if plotUses[i] > 0.1 and plotUses[i] < 0.9 :\n",
    "        print(v,tractPop[v], plotUses[i],\"vtd no, its pop, and usage across all units\")\n",
    "        plotPoly(tractGeom[v])\n",
    "unused = list()\n",
    "for v in range(nVTDs):\n",
    "    if vtdUSE[v] < 0.2 and MAP.contains(vtdGeom[v].centroid) and tractPop[v] > 0:\n",
    "        unused.append(v)\n",
    "        #print(v,\"in county\",countyNo[v],\"has pop\",tractPop[v],\"and map-total usage of\",vtdUSE[v],\"its surroundedness is\",v in surroundedVTDs)\n",
    "        plotPoly(vtdGeom[v].centroid.buffer(0.1))\n",
    "        plotCenter(v,vtdGeom[v],8)\n",
    "    #if vtdUSE[v] > 0.2 and vtdUSE[v] < 0.95:\n",
    "    #    plotCenter(r3(vtdUSE[v]),vtdGeom[v])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "3d2a393c-5ab8-4140-80eb-1153c2ef41f9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u]  < 0.9:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "    if  unitUse[u]  > 1.1:\n",
    "        plotPoly(unitGeom[u],1.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "404935e6-f0de-4b51-9db9-020aa208f852",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integrity check: vtd-based pops.  These should all be within single digits\n",
      "x = n surrounded, y= unit - vtd-based\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t, HDunit-based pop - pop from vtd-based HDs 541 -12.509\n",
      "t, HDunit-based pop - pop from vtd-based HDs 2330 -12.453\n",
      "t, HDunit-based pop - pop from vtd-based HDs 3575 -12.452\n",
      "t, HDunit-based pop - pop from vtd-based HDs 3579 -12.018\n",
      "t, HDunit-based pop - pop from vtd-based HDs 4003 -12.415\n",
      "t, HDunit-based pop - pop from vtd-based HDs 5670 -12.109\n",
      "t, HDunit-based pop - pop from vtd-based HDs 5671 -12.121\n",
      "t, HDunit-based pop - pop from vtd-based HDs 5682 -12.07\n",
      "t, HDunit-based pop - pop from vtd-based HDs 5712 -12.319\n",
      "Here are the HD centers with significant pop difference between unit-based and vtd-based HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"integrity check: vtd-based pops.  These should all be within single digits\")\n",
    "HDvtdbasedPop = [0. for t in range(nHDs)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "nSurrs = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "        if u in surroundedVTDs:\n",
    "            nSurrs[t] += 1\n",
    "    for v in HDfullVTDlist[t]:\n",
    "        HDvtdbasedPop[t] += origVTDpop[v] #tractPop[v]\n",
    "    for i,v in enumerate(HDpartialVTDlist[t]):\n",
    "        HDvtdbasedPop[t] += HDvtdFrac[t][i] * origVTDpop[v] #tractPop[v] also works\n",
    "        \n",
    "plt.scatter([nSurrs[t] for t in popHDlist], [HDvPop[t] - HDvtdbasedPop[t] for t in popHDlist] )\n",
    "print(\"x = n surrounded, y= unit - vtd-based\")\n",
    "plt.show()\n",
    "plotThis = False\n",
    "for t in popHDlist:  #seems like for TN, we lost a vtd in converting from unit-based to vtd-based\n",
    "    if abs(HDvPop[t] - HDvtdbasedPop[t]) > 12:  #10  #12\n",
    "        plotThis = True\n",
    "        print(\"t, HDunit-based pop - pop from vtd-based HDs\",t,r3(HDvPop[t] - HDvtdbasedPop[t]) )\n",
    "        plotPoly(tractCP[t].buffer(0.1))\n",
    "if plotThis:\n",
    "    plotPoly(MAP)\n",
    "    print(\"Here are the HD centers with significant pop difference between unit-based and vtd-based HD lists\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef27af54-daf5-4e8f-9230-bce5b0b1e705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for WI\n",
      "In year/election 2020 Dem and GOP total votes were 1630058 1609642 for a stateGOP of 0.49685\n",
      "There are a total of 7059  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 1382123 1404922 for a stateGOP of 0.50409\n",
      "There are a total of 7059  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f628069d-4177-401e-bf49-b7f194d0ef8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for WI\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv WI7059patchedVTDs.csv\n",
      "enter the number of Congr'l districts in the state; e.g. 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 7059 drawn districts.  This state has 8 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n",
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv\")\n",
    "\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of Congr'l districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"partials\" in HDdf.columns.values: #\"splitTractNo\" #.to_list():\n",
    "    splitTractList, splitTractUseList = HDdf['partials'], HDdf['HDvtdFrac']\n",
    "    splitTractNo = [ast.literal_eval(splitTractList[t])    for t in range(nRows)]\n",
    "    splitTractUse = [ast.literal_eval(splitTractUseList[t]) for t in range(nRows)]\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [[] for t in range(nRows)] , [ [] for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDweight)) )\n",
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = [ str( tractPopFile['GEOID20'][i]) for i in range(len(tractPopFile['GEOID20'])) ] #force strings to match\n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "mergedGEO = [str(mergedDF['GEOID20'][i]) for i in range(len(mergedDF['GEOID20'])) ]  #force strings to match\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedGEO, \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Dem-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"sanity check - Dem-leaning vtds for year\",years[0])  #for MA, do GOP-leaning.  Other states, use Dem-leaning\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if DemVotes[0][vestID[v]] > RepVotes[0][vestID[v]]:\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"D\", color = \"blue\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 3000\n",
      "working on drawn district no 4000\n",
      "working on drawn district no 5000\n",
      "working on drawn district no 6000\n",
      "working on drawn district no 7000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 1630058 1609642 -20416\n",
      "ensemble : 1623421 1618660 -4760\n",
      "the true and ensemble state GOP leans are 0.49685 0.49926585632197185\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDweight)  #now including cut districts\n",
    "nMapDistricts = nCutDistricts + nDistricts\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nMapDistricts* HDweight[t] * ( np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([DemVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "    nEnsembleReps[y] += nMapDistricts* HDweight[t] * ( np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([RepVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "5c607c63-df0d-4334-8131-368c090c76d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total drawn districts, HD-drawn, map districts 2466 2465 11\n"
     ]
    }
   ],
   "source": [
    "print(\"total drawn districts, HD-drawn, map districts\",nDrawnDistricts,nHDs, nMapDistricts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb0d0d12-6bf4-4d5f-9236-fa8735393e98",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
